Battery adaptive charging using battery physical phenomena

ABSTRACT

Systems and apparatus may carry out analysis of battery physical phenomena, and characterize batteries based on phenomena occurring in particular time and/or frequency domains. These systems may be additionally responsible for charging and/or monitoring a rechargeable battery. Examples of battery physical phenomena include mass transport (e.g., diffusion and/or migration) in battery electrolytes, mass transport in battery electrodes, and reactions on battery electrodes.

CROSS REFERENCE TO RELATED PATENT APPLICATION

An Application Data Sheet is filed concurrently with this specificationas part of the present application. Each application that the presentapplication claims benefit of or priority to as identified in theconcurrently filed Application Data Sheet is incorporated by referenceherein in its entirety and for all purposes.

BACKGROUND

Batteries and associated charging circuitry are used in many settingsand their use continues to grow. Lithium ion batteries are now widelyused in many facets of commerce, from powering nearly all portableelectronic devices to fully or partially powering many vehicles such asautomobiles.

Rechargeable batteries and associated control logic have been engineeredto facilitate efficient charging, high capacity, and long life.Unfortunately, a variety of factors reduce the ability of batteries tofully achieve all of these features. Variations in manufacturing and enduse lead to wide variations in the ability of any given battery to haveboth a long cycle life and possess fast charging times.

Characterizing a battery's current state of health and/or determiningits future performance would be useful in many contexts.

SUMMARY

Certain aspects of this disclosure pertain to methods of adaptivelycharging a battery. Such methods may be characterized by the followingoperations: (a) applying a stimulus to the battery; (b) measuring thebattery's response to the stimulus during a time regime or a frequencyregime where the battery's response reflects a physical phenomenonoccurring in the battery; (c) using the battery's response, as measuredin (b), to characterize the physical phenomenon; and (d) based on thephysical phenomenon's characterization, as determined in (c), adapting acharging process of the battery.

The methods may additionally include conducting a first portion of thecharging process prior to (a), and adapting the charging process of thebattery may involve modifying a charge signal applied to the battery. Asan example, modifying the charge signal applied to the battery mayinvolve modifying one or more current steps or current pulses that areused in the charging process.

In certain embodiments, the stimulus includes an oscillating current. Asan example, the oscillating current may be applied at multiplefrequencies. In certain embodiments, the stimulus includes an edge inapplied electrical current.

In some implementations, measuring the battery's response to thestimulus in (b) is made during the time regime where the battery'sresponse reflects the physical phenomenon occurring in the battery. Incertain implementations, measuring the battery's response to thestimulus in (b) includes taking multiple measurements of the battery'sresponse over a defined duration associated with the physical phenomenonoccurring in the battery. In some cases, measuring the battery'sresponse to the stimulus in (b) is made during the frequency regimewhere the battery's response reflects the physical phenomenon occurringin the battery.

In certain embodiments, the battery's response to the stimulus comprisesa voltage measured across terminals of the battery. As an example, thevoltage measured across the terminals may include (i) a phase withrespect to an applied oscillating current, which is the stimulus, and(ii) an amplitude. As a further example, the voltage measured across theterminals may include a value taken during the time regime where thebattery's response reflects the physical phenomenon occurring in thebattery.

In certain embodiments, the physical phenomenon includes transport ofmetal ions in an electrolyte of the battery. In certain embodiments, thephysical phenomenon includes transport of metal ions in an electrode ofthe battery. In certain embodiments, the physical phenomenon includes achemical or electrochemical reaction in or on an electrode of thebattery.

In some cases, methods additionally include the following operations:(e) measuring the battery's response to the stimulus during a secondtime regime or a second frequency regime where the battery's responsereflects a second physical phenomenon occurring in the battery; and (f)using the battery's response, as measured in (e), to characterize thesecond physical phenomenon. In such cases, adapting the charging processof the battery in (d) may be based on both the physical phenomenon'scharacterization, as determined in (c) and the second physicalphenomenon's characterization, as determined in (f). In one example, thephysical phenomenon includes transport of metal ions in an electrode ofthe battery and wherein the second physical phenomenon comprisestransport of metal ions in an electrolyte of the battery.

In certain embodiments, operation (c) includes determining a chargepulse voltage from the battery's measured response to characterizetransport of metal ions in an electrode of the battery.

In certain embodiments, operation (c) includes determining a partialrelaxation time from the battery's measured response to characterizetransport of metal ions in an electrolyte of the battery.

Some aspects of this disclosure pertain to systems for adaptivelycharging a battery including at least two terminals. Such systems may becharacterized by the following features:

a. charging and/or monitoring circuitry designed or configured to applya charge signal to the battery, and measure a voltage at the terminalsof the battery; andb. control circuitry, coupled to the charging and/or monitoringcircuitry designed or configured to cause the system to: (a) apply astimulus to the battery; (b) measure the battery's response to thestimulus during a time regime or a frequency regime where the battery'sresponse reflects a physical phenomenon occurring in the battery; (c)use the battery's response, as measured via (b), to characterize thephysical phenomenon; and (d) based on the physical phenomenon'scharacterization, as determined in (c), adapt a charging process of thebattery.

The control circuitry is designed or configured to cause any appropriatepart of the battery charging system to perform any one or more ofoperations (a)-(d). This includes implementations when the controlcircuitry itself performs some or all of any of the operations.

In certain embodiments, the control circuitry is designed or configuredto cause the system to adapt the charging process of the battery in (d)by causing the system to modify a charge signal applied to the battery.In some cases, the control circuitry is further designed or configuredto cause the system to conduct a first portion of the charging processprior to (a). In some cases, the control circuitry is designed orconfigured to cause the system to modify the charge signal applied tothe battery by causing the system to modify one or more current steps orcurrent pulses that are used in the charging process.

In certain embodiments, the stimulus comprises an oscillating current.In some cases, the control circuitry is designed or configured to causethe system to apply the oscillating current at multiple frequencies. Incertain embodiments, the stimulus includes an edge in applied electricalcurrent.

In certain embodiments, the control system is designed or configured tocause the system to measure the battery's response to the stimulus in(b) during the time regime where the battery's response reflects thephysical phenomenon occurring in the battery. In certain embodiments,the control system is designed or configured to cause the system tomeasure the battery's response to the stimulus in (b) by causing thesystem to take multiple measurements of the battery's response over adefined duration associated with the physical phenomenon occurring inthe battery. In certain embodiments, the control system is designed orconfigured to cause the system to measure the battery's response to thestimulus in (b) during the frequency regime where the battery's responsereflects the physical phenomenon occurring in the battery.

In certain embodiments, the battery's response to the stimulus includesa voltage measured across terminals of the battery. In some cases, thevoltage measured across the terminals includes (i) a phase with respectto an applied oscillating current, which is the stimulus, and (ii) anamplitude. In some cases, the voltage measured across the terminalsincludes a value taken during the time regime where the battery'sresponse reflects the physical phenomenon occurring in the battery.

In certain embodiments, the physical phenomenon includes transport ofmetal ions in an electrolyte of the battery. In certain embodiments, thephysical phenomenon includes transport of metal ions in an electrode ofthe battery. In certain embodiments, the physical phenomenon includes achemical or electrochemical reaction in or on an electrode of thebattery.

In certain embodiments, the control circuitry is further designed orconfigured to cause the system to: (e) measure the battery's response tothe stimulus during a second time regime or a second frequency regimewhere the battery's response reflects a second physical phenomenonoccurring in the battery; and (f) use the battery's response, asmeasured in (e), to characterize the second physical phenomenon. In suchembodiments, the control system may be designed or configured to useboth the physical phenomenon's characterization, as determined in (c)and the second physical phenomenon's characterization, as determined in(f) in determining how to cause the system to adapt the charging processof the battery in (d). In one example, the physical phenomenon includestransport of metal ions in an electrode of the battery and wherein thesecond physical phenomenon includes transport of metal ions in anelectrolyte of the battery.

In certain embodiments, the control system is designed or configured tocharacterize the physical phenomenon in (c) by causing the system todetermine a charge pulse voltage from the battery's measured response inorder to characterize transport of metal ions in an electrode of thebattery. In certain embodiments, the control system is designed orconfigured to characterize the physical phenomenon in (c) by causing thesystem to determine a partial relaxation time from the battery'smeasured response in order to characterize transport of metal ions in anelectrolyte of the battery.

These and other features of the disclosure will be described below, inmore detail, with reference to the associated drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

In the course of the descriptions to follow, reference will be made tothe attached drawings. These drawings show different aspects of someimplementations, and where appropriate, reference numerals illustratinglike structures, components, materials and/or elements in differentfigures are labeled similarly. It is understood that variouscombinations of the structures, components, and/or elements, other thanthose specifically shown, are contemplated and are within the scope ofthe present disclosure.

The present disclosure is neither limited to any single aspect norembodiment thereof, nor to any combinations and/or permutations of suchaspects and/or embodiments. Moreover, each of the aspects of the presentdisclosure, and/or embodiments thereof, may be employed alone or incombination with one or more of the other aspects of the presentdisclosure and/or embodiments thereof. For the sake of brevity, certainpermutations and combinations are not discussed and/or illustratedseparately herein.

FIG. 1 illustrates, in block diagram form a “battery charging system” ora “battery monitoring system” in conjunction with a battery wherecharging circuitry 112 (including, e.g., a voltage source and/or currentsource) responds to control circuitry 116 which receives batteryinformation from monitoring circuitry 114 (including, e.g., a voltmeterand/or a current meter).

FIG. 2 is an illustration depicting three responses to a charge packethaving a charge pulse (which injects charge into the battery) and adischarge pulse (which removes charge from the battery) wherein a firstresponse (A) includes a significant “overshoot” whereby the dischargepulse removed too little charge from the battery, a second response (B)includes no significant “overshoot” or “undershoot” wherein thedischarge pulse removes a suitable amount of charge which provides thefastest partial relaxation time of the three responses, and a thirdresponse (C) includes a significant “undershoot” whereby the dischargepulse removes too much charge from the battery.

FIGS. 3a-3d illustrate current waveforms of charge signals that may beused to charge a battery.

FIGS. 4a-4g depict charge and discharge packets of charging anddischarging signals.

FIGS. 5a-b depict current and voltage waveforms resulting from charginga battery using a constant-current constant-voltage (CCCV) technique andan adapted CCCV technique which includes a plurality of constant chargepulses. Adapting a CCCV technique may involve modifying one or morecharacteristics of a constant-current portion of the charge process. Anexample of such modification includes changing the magnitude of theapplied current, which may involve changing the current magnitude orduration in one or more steps if the constant-current portion isimplemented as current steps. Another example may involve changing thecriteria for transitioning from the constant-current to theconstant-voltage portion of the charge process.

FIG. 5c depicts a simple example of a battery model for relating batterycharge process parameter values to battery charge processcharacteristics or classifications.

FIG. 6 is a Nyquist plot for electrochemical impedance spectroscopyshowing the contributions of various battery phenomena on measuredimpedance over a range of frequencies.

FIG. 7a presents an example process flow for implementing an in situfrequency domain analysis of a battery.

FIG. 7b presents an example process flow for implementing an in situtime domain analysis, at least partially, of a battery.

FIG. 7c illustrates time domain acquisition of electrochemical data andcorresponding frequency domain information as illustrated using aNyquist plot.

FIG. 8a illustrates a charge sequence having two charge pulses (eachincluding a charging period (T_(charge))) followed by a rest period(Trent) where the period of the charge sequence is identified asT_(packet), according to certain aspects of the present disclosure; aterminal voltage response of the battery/cell to such charge sequence isillustrated where a first voltage (V₁) is identified (which correlatesto the beginning of the first charge pulse and, in this embodiment, thebeginning of the sequence), a second voltage (V₂) is identified (whichcorrelates to the end of the first charge pulse and/or the peak of thechange in the terminal voltage due to the first charge pulse), a thirdvoltage (V₃) is identified (which correlates to the beginning of thesecond charge pulse), a fourth voltage (V₄) is identified (whichcorrelates to the end of the second charge pulse and/or the peak of thechange in the terminal voltage due to the second charge pulse) and afifth voltage (V₅) is identified (which correlates to when the terminalvoltage of the battery/cell decays to a predetermined value (forexample, less than about 10% of peak deviation relative to the terminalvoltage of the battery/cell when the charge/discharge sequence isapplied (here, V₁) or less than 5% of such peak deviation); where thepartial relaxation time (PRT) of the battery/cell due to the chargesequence may be the amount of time between (i) the termination/end ofthe second charge pulse and/or the peak of the change in the terminalvoltage due to the second charge pulse and (ii) when the terminalvoltage of the battery/cell decays to a predetermined value (forexample, less than 10% of peak deviation, or less than 5% of peakdeviation).

FIG. 8b illustrates an exemplary charge sequence having a charge pulse(which injects charge into the battery/cell) and a discharge pulse(which removes charge from the battery/cell) where the charge pulseincludes a charging period (T_(charge)) and the discharge pulse includesa discharging period (T_(discharge)), according to certain aspects ofthe present disclosure; notably, in this charge sequence, anintermediate rest period (T_(inter)) is disposed between the charge anddischarge pulses, and a rest period (Trent) is disposed after thedischarge pulse and before the next sequence; an exemplary terminalvoltage response of the battery/cell to such charge sequence isillustrated where a first voltage (V₁) is identified (which correlatesto the beginning of the charge pulse and, in this embodiment, thebeginning of the sequence), a second voltage (V₂) is identified (whichcorrelates to the end of the charge pulse and/or the peak of the changein the terminal voltage due to the charge pulse), a third voltage (V₃)is identified (which correlates to the end of the discharge pulse and/orthe peak of the change in the terminal voltage due to the dischargepulse) and a fourth voltage (V₄) is identified (which correlates to whenthe terminal voltage of the battery/cell decays to a predetermined value(for example, preferably less than 10% of peak deviation relative to theterminal voltage of the battery/cell when the charge/discharge sequenceis applied (here, V₁) and, more specifically, less than 5% of peakdeviation); where the relaxation time of the battery/cell due to thecharge sequence may be represented as the amount of time between (i) thetermination/end of the discharge pulse and/or the peak of the change inthe terminal voltage due to the discharge pulse (see, V₃ and T₁) and(ii) when the terminal voltage of the battery/cell decays to apredetermined value (for example, preferably less than 10% of peakdeviation and, more preferably, less than 5% of peak deviation) (see, V₄and T₂); notably some or all of the characteristics of the charge pulses(for example, pulse amplitude, pulse width/duration and pulse shape) areprogrammable and/or controllable via charging circuitry where theamplitude of the positive and/or negative pulses may vary within thecharge sequence (and are programmable and/or controllable), the durationand/or timing of the rest periods may vary within the sequence (and areprogrammable and/or controllable) and/or, in addition, such pulses maybe equally or unequally spaced within the sequence; the combination ofcharging pulses, discharging pulses and rest periods may be repetitiveand thereby forms a sequence that may be repeated; all combination orpermutations of pulse, pulse characteristics, periods, sequences andsignal characteristics and configurations are intended to fall withinthe scope of the present disclosure; moreover, discharge sequences mayhave similar characteristics as charge sequences except, however, a netcharge is removed from the battery/cell; for the sake of brevity, thediscussion/illustration with respect to discharge sequence will not berepeated. All of these possible combinations may be applied as part ofan adaptive charging process.

FIG. 8c illustrates a charge sequence like that of FIG. 8b where thesequence includes a charge pulse (which injects charge into thebattery/cell) and a discharge pulse (which removes charge from thebattery/cell) where the charge pulse includes a charging period(T_(charge)) and the discharge pulse includes a discharging period(T_(discharge)), according to certain aspects of the present disclosure;in this illustration, a partial relaxation time corresponding to thecharge pulse of the sequence is also depicted (see, Relaxation time)where one measure of the relaxation time associated with the chargepulse is equal to the difference between T_(A) (which coincides with V₂)and T_(B) (which coincides with V₄). Another measure of relaxation timeis the time between the end of the discharge pulse or edge and the pointwhen the voltage value has decayed to the predetermined value (e.g.,T_(B)-T₁). Regardless of how it is measured, the relaxation time of thebattery/cell in response to the charge sequence having a charge pulseand discharge pulse may be shorter than the relaxation time of thebattery/cell in response to the charge sequence not having a dischargepulse (compare T_(B)-T₁ of FIG. 8c and T₂-T₁ of FIG. 8a ) and, as such,under certain circumstances, the total charging time of a chargingsequence having charge and discharge pulses may be shorter than thecharging time of a charging sequence having no discharge pulses toshorten or reduce the relaxation time.

DETAILED DESCRIPTION Introduction

In various embodiments, data obtained from batteries is considered inone or more time domains characteristic of physical phenomena such asdiffusion of ions in a battery electrolyte, diffusion of ions in anelectrode matrix (e.g., carbon in the negative electrode of a lithiumion battery), and electrochemical reactions at the interface of theelectrolyte and a battery electrode. To this end, a battery may beprobed in a manner allowing a battery monitoring and/or charging systemto obtain data that characterizes at least two or three of thesedifferent battery phenomena. In some cases, the battery's response to astimulus is analyzed in the frequency domain. In some such cases, thebattery is probed at different applied current or voltage frequencies.In some cases, battery data is collected at different times afterapplication of a stimulus (e.g., a current pulse/edge). In one example,the battery data is or includes a battery's charge pulse voltage(“CPV”), which may provide information reflective of diffusion in thebattery's solid electrode material. In another example, the battery datamay be a battery's partial relaxation time, which provides informationreflective of transport in the electrolyte. In various embodiments, thebattery is monitored, and data is collected, during charging of thebattery. In some cases, the charging and monitoring is accomplished byusing a pulsed charge current.

Systems and apparatus may be designed and/or configured to carry outanalysis of battery physical phenomena, and characterize batteries basedon phenomena occurring at one of the above-mentioned time and/orfrequency domains. These systems may be additionally responsible forcharging and/or monitoring a rechargeable battery.

Terminology

The term “battery” as used herein refers to one or more galvanic cells(each of which stores energy electrochemically). A battery may be anindividual cell and/or a plurality of cells arranged electrically in aseries and/or parallel configuration. Although some references describea battery as including two or more cells, the term “battery” is not solimited in this disclosure. In some implementations, a battery is asingle cell or multiple cells connected in series or parallel to providea desired voltage or current rating. Batteries considered herein aretypically rechargeable (secondary batteries).

A battery generally contains an anode, a cathode, and an electrolyte orseparator. In some contexts, for galvanic electrochemical systems suchas batteries, the anode is referred to as the negative electrode and thecathode is referred to as the positive electrode. In operation of abattery, an electrolyte conducts ions but not electrons. Duringdischarge, the negative electrode is oxidized and donates electrons toan external circuit, while the positive electrode is reduced andconsumes electrons from an external circuit. During charge, theprocesses are reversed. In some cases, the negative electrode is anintercalation anode that includes an intercalation matrix or substratesuch as carbon, tin, and/or silicon that is configured to insert orintercalate ions during charge. These ions are typically alkali metalions (e.g., lithium or sodium ions) or alkaline earth metal ions. Othertypes of battery chemistries or materials may be used in the methods andapparatus of the present disclosure.

An “electronic device” as indicated herein refers to a device thatperforms any number of tasks or functions electrically and that can bepowered by a battery. The device may or may not physically include(e.g., enclose or attach) the battery, battery charging system, orcontrol logic described herein. Electronic devices may be portable orfixed. Examples of electronic devices include mobile phones, digitalcameras, laptops, portable speakers, battery powered vehicles, systemsfor storing solar and other generated electrical energy, uninterruptiblepower supplies, and power tools.

“Battery parameters” refer to parameters of, or associated with, abattery and its use. Values of battery parameters are often obtainedand/or used by battery control logic such as logic used in a batterycharger. Examples of types of battery parameters include charge pulsevoltage, partial relaxation time, time in service for the battery (e.g.,from the time it was installed in the device it powers or when it wasfirst used), and full charge capacity, and projected capacity (typicallyto some number of cycles. Other battery parameters may reflect batteryphysical properties such as material transport in an electrode orelectrolyte (e.g., diffusion coefficients), reactions or processeswithin or at the interface of an electrode (e.g., rate constants anddouble layer capacitance), etc. The values of each of these parametersmay vary as a function of the state of charge during the charge portionof a single battery cycle or operating temperature. The parametersvalues may also vary from cycle-to-cycle over the battery's life.

“Battery type” distinguishes classes or groups of batteries from oneanother. Among the factors that identify a battery type are (i) batterychemistry (e.g., lithium ion batteries and nickel metal hydridebatteries), (ii) battery format (e.g., cylindrical versus prismaticversus pouch) and size (e.g., 18650 versus AA), (iii) manufactureridentity (e.g., Samsung SDI versus Panasonic), (iv) manufacturingprocess, and (v) manufacturer process implementation (e.g. lot, plant,and/or site). An example of a battery type is an 18650 formatrechargeable lithium-ion battery produced by a particular manufacturer(e.g., Samsung SDI, LG Chemical, Murata Energy, etc.) produced in aparticular lot using a particular process of the manufacturer. Any oneor more of the above factors may be used to define a battery type.Further, the factors may be defined specifically. For example, lithiumion batteries may be divided into types of negative electrodes such asgraphite, silicon, and tin or tin oxide.

A “charge process” or “charging process” refers to a process in which abattery is charged from a state of less charge to a state of morecharge. During a charge process, the battery's state of chargeincreases. A charge process may be conducted under the control ofcharging circuitry which may be part of the battery charging system orthe battery control logic. In certain embodiments, charging circuitryadapts, adjusts and/or controls the amplitude, pulse width, duty cycle,or other parameter of charging or discharging current pulses and/or itadjusts and/or controls the conditions of a constant voltage portion ofthe charge process. It may perform any such function to control oradjust a feature of the battery such as the battery's overall chargingrate, cycle life, etc. It may perform these functions to control oradjust a more specific characteristic of the battery such as thebattery's relaxation time, characteristics of the decay of the terminalvoltage (e.g., the rate of decay or the shape of the decay curve),propensity to plate metallic lithium, etc. For example, as depicted inFIG. 2, charging circuitry may adapt, adjust and/or control theamplitude and pulse width of the discharge pulse to reduce or minimizethe “overshoot” or “undershoot” of the decay of the terminal voltage ofthe battery.

A “charge cycle” is the process of charging a rechargeable battery anddischarging it with a particular load. A charge cycle may involvecharging and discharging an amount of charge that is equivalent ornearly equivalent to the battery's capacity, but not necessarily by onefull charge and one full discharge. For instance, using half the chargeof a fully charged battery, recharging it, and then using the sameamount of charge again, and then subsequently recharging it may count asone charge cycle. The number of charge cycles until a battery failsindicates how many times a rechargeable battery can undergo the processof complete charging and discharging until failing certain criteria. Thenumber of charge cycles may be used to specify a battery's expectedlife, which may affect battery life more than the mere passage of time.

A “charge signal” refers to the electrical current (e.g., the currentwaveform) that passes through the terminals of a battery as a result ofcircuitry configured to apply charge (a charging signal) or removecharge (a discharging signal) from a battery. In various embodiments,one or more charge signals are applied to a battery to charge it, aspart of a charge process. A charging or recharging sequence, operation,process, or cycle may include one or more charge signals, which, intotal, inject or apply charge into the battery and, optionally, one ormore discharge signals (e.g., discharge signals), which, in total,remove charge from the battery. A charge signal may include a pluralityof charge packets and/or discharge packets. Each charge packet mayrepresent a portion of a charge sequence and contain one or more chargepulses, discharge pulses and rest periods. Current variations such asedges and pulses may be provided as independent features, outside theconcept of a charge packet. Regardless of whether they are part of acharge packet, pulses of a charge signal may be any shape (for example,rectangular, triangle, sinusoidal or square). In some cases, a chargepulse has a temporal duration of between about 1 ms to about 5,000 ms.

“Battery Control Logic” refers to the control algorithms and/or rulesthat are used to determine (i) charging parameters (for example, theamplitude, width, and frequency of charge and discharge pulses) in thecharge process, and/or (ii) information about a battery's health,expected life, defects, its physical and/or material properties, etc. Insome embodiments, the algorithms or rules are chosen to improve orbalance a battery's cycle life and/or charge speed. In some cases,battery control logic may determine or estimate a battery's state ofcharge (SOC), state of health (SOH), partial relaxation time,overpotential, or whether metal plating has occurred. In some cases,battery control logic may make use of state of health (SOH) informationand/or battery feedback measurements that may include the state ofcharge (SOC), temperature, voltage, current, and the voltage responseshape due to charging and discharging cycles. In some cases, batterycontrol logic employs a battery model to classify a battery and/or thebattery when subject to a defined set of charging conditions (e.g.,battery charge process parameter values). In certain embodiments,battery control logic is implemented as executable instructions or codestored in hardware (e.g., any of various forms of memory), firmware, orsoftware. The battery control logic may also be considered to includeone or more processors configured or designed to execute theinstructions or code, particularly when such processors are directlylinked to the memory or other storage providing the instructions orcode. Unless otherwise stated, the terms battery control circuitry andcontrol circuitry are equivalent to battery control logic. In certainembodiments, battery control logic is part of a battery charging system.

A “battery monitoring system,” which may be part of a battery chargingsystem, is used to monitor a battery and use measured frequency or timedomain battery data obtained from the battery (and/or characterizingconditions under which the battery is charged or otherwise operated). Invarious embodiments, the monitoring system provides information to thebattery control logic to characterize a battery and/or determineappropriate charging conditions. FIG. 1 depicts in block form an examplebattery charging system that includes charging circuitry 112 thatresponds to control circuitry 116 (e.g., battery control logic) thatreceives battery information from monitoring circuitry 114. FIG. 1 isdescribed in more detail below.

“Capacity” or nominal capacity refers to the total charge (which may bemeasured in Amp-hours or coulombs) available when the battery isdischarged at a certain discharge current (which may be specified as aC-rate) from a fully charged state (e.g., 100 percent state-of-charge)to a defined cut-off voltage. A battery's capacity may change overmultiple charge cycles. In conventional batteries, it is common for thebattery's capacity to decrease or “fade” over multiple cycles.

The term “capacity fade” refers to reduction of battery capacity overtime or multiple charge cycles. A battery's capacity at any given cyclemay be based on the maximum battery capacity, at that cycle, or otherreference value of battery capacity (e.g., 85% of initial maximumcapacity, capacity at specific terminal voltage, etc.)

“Terminal voltage” is the voltage between the battery terminals.Terminal voltage may vary with state of charge and/or the magnitude ofdischarge or charge current. The terminal voltage may be measured withor without current flowing through a load. In the latter case, theterminal voltage is an open circuit voltage.

An “open circuit voltage” (OCV) is the terminal voltage of a battery inthe absence of current flow. It is a property of the cell under aparticular set of conditions. A closed circuit voltage (CCV) is thebattery terminal in the presence of current flow (e.g., during chargingof the battery). CCV is affected by OCV, but also depends on theoperation of the battery. For example, during constant current charging,a CCV may be calculated as the sum of the OCV and the charging currentmultiplied by the resistance of the battery. During constant voltagecharge, the CCV is equal to the applied voltage.

“State of charge” (SOC) may refer to the amount of charge currentlystored in a battery as a percentage of maximum capacity. SOC is used tocharacterize how far a battery in use has progressed between a fullycharged state and a discharged state. In some cases, state of charge iscalculated using current integration to determine the present amount ofcharge in a battery.

The “state of health” (SOH) of a battery is a parameter thatcharacterizes the “age” or “health” of the battery and/or ability of thebattery to hold charge, for example, relative to a given point in thebattery's operation (for example, the initial time in operation). TheSOH of a battery may provide information to estimate, calculate,measure, and/or determine other battery parameters such as the abilityof a battery to hold a charge. The voltage at the terminals of thebattery at a given SOC changes as the SOH changes, and hence the voltagecurve (voltage versus state of charge) of the battery shifts as it agesand its SOH deteriorates. The state of health parameter is furtherdescribed in U.S. Pat. No. 9,121,910, issued Sep. 1, 2015, which isincorporated herein by reference in its entirety.

A “charge pulse voltage” (CPV) is a voltage measurement that may becharacterized as (i) a peak voltage, measured at the terminals of thebattery/cell, which is produced by the battery in response to a changein current (e.g., an edge or pulse) to which the battery voltageresponses, and/or (ii) a substantial peak voltage (e.g., within 5-10% ofthe peak voltage), measured at the terminals of the battery/cell, whichis produced by the battery in response to a charge pulse. In some cases,a CPV measurement is used by an adaptive charging process. In somecases, a CPV measurement is taken to determine a battery parameter suchas SOC or SOH.

A “battery model” or simply a “model” is mathematical construct,software, and/or other logic that may classify a battery or a particularset of charge process parameters applied to or characterizing thebattery. Examples of such parameters include a battery's state ofcharge, temperature, charge voltage, open circuit voltage, chargecurrent, the properties and state of its internal materials, thebattery's design, etc. The model takes as inputs information about thebattery itself and/or the charge process parameters and outputs one ormore charge process characteristics of the battery. The chargecharacteristics may represent a conclusion about the appropriateness ofthe charge process parameters (e.g., safe, potentially unsafe, or unsafecharging conditions) and/or a prediction about the results or effects ofthe charge process parameters on the battery; e.g., the effects ofsubjecting the battery to the input set of charge process parameters.

A model may be applicable to just a particular individual battery or toa plurality of batteries of the same battery type or within a group ofrelated battery types. In some cases, a model accounts for the state ofhealth of a battery. For example, if irreversible damage to the batterycell has occurred, a model may reflect the battery's state of health.More generally, the model may evolve or learn based on informationand/or data it gains from application to one or more batteries. Somechanges to the model may result from changes in a battery itself, e.g.,changes in its health or material properties, as mentioned. Otherchanges to the model may result from observing and incorporatingdifferent situations encountered during battery charging. Such observingand learning may be implemented as machine learning or deep learning.

A model may take any of various forms. In one example, the model takesthe form of a lookup table. In another example, the model takes the formof one or more expressions, matrices, etc. such as regressionrelationships, neural networks, decision trees, and the like.

“Measuring,” “collecting,” or “capturing” a parameter as stated hereinis a way of obtaining a value of the parameter. For instance, measuringthe voltage of a battery can mean using an instrument such as avoltmeter to directly measure the voltage between terminals of thebattery. In some contexts, it means obtaining parameter values relatedto raw measurements of the battery and/or deriving other informationabout the battery (e.g., partial relaxation, battery swelling, etc.).Raw measurements of a battery may include current (applied orgenerated), charge accepted or passed, voltage, and temperature.

Numeric ranges are inclusive of the numbers defining the range. It isintended that every maximum numerical limitation given throughout thisspecification includes every lower numerical limitation, as if suchlower numerical limitations were expressly written herein. Every minimumnumerical limitation given throughout this specification will includeevery higher numerical limitation, as if such higher numericallimitations were expressly written herein. Every numerical range giventhroughout this specification will include every narrower numericalrange that falls within such broader numerical range, as if suchnarrower numerical ranges were all expressly written herein.

The headings provided herein are not intended to limit the disclosure.

Unless defined otherwise herein, all technical and scientific termsherein have the same meaning as commonly understood by one of ordinaryskill in the art. Various scientific dictionaries that include the termsincluded herein are well-known and available to those in the art.Although any methods and materials similar or equivalent to thosedescribed herein find use in the practice or testing of theimplementations disclosed herein, some methods and materials aredescribed.

As used herein, the singular terms “a,” “an,” and “the” include theplural reference unless the context clearly indicates otherwise.

The logical connector “or” as used herein is inclusive unless specifiedotherwise. As such, condition “A or B” is satisfied by “A and B” unlessspecified otherwise.

Adaptive Charging

Adaptive charging as described herein refers to charging processes thatmake use of feedback related to battery conditions, environmentalconditions, user behavior, user preferences, battery diagnosticinformation, physical properties of the battery and the like. Usingadaptive charging techniques, one or more characteristics of a chargesignal may be continuously or periodically adjusted or controlled whilecharging a battery. Such adjustment or control may be performed tomaintain battery parameter values within a selected range. Generally,adaptive charging is used to optimize the battery's cycle life, optimizeits charge speed, minimize its swelling, and/or keep it operating withinsafe boundaries. For example, adaptive charging may keep a batterycharge process operating in a regime where minimal or no batterydegradation, such as from metal plating (e.g., metallic lithiumplating), occurs or is likely to occur. Various types of batteryparameter values may be captured and used for adaptive charging. Some ofthese parameter values are obtained by measuring parameters directlyassociated with the battery, charging system, and/or the device poweredby the battery. For example, parameter values may be obtained frombattery terminal voltage measurements, battery temperature, batterysize, and the like. In some cases, adaptive charging also makes use ofparameters not directly associated with a battery. Examples include userinformation and environmental information. Examples of indirectlyobtained battery parameters that may be used for adaptive charginginclude charge pulse voltage, partial relaxation time, the state ofcharge, and the battery's state of health. In some cases, ranges ofacceptable values of each of these parameters may vary as a function ofthe state of charge during the charge portion of a battery cycle. Theparameters values may also vary from cycle-to-cycle over the battery'slife. In some cases, adaptive charging may also make use of the currentcharging parameters such as the current or voltage that is being appliedto a battery by charging circuitry.

Various adaptive charging techniques are described in applicationsassigned to Qnovo Inc. of Newark, Calif. Examples of such patentsinclude U.S. Pat. No. 8,638,070, titled “METHOD AND CIRCUITRY TOADAPTIVELY CHARGE A BATTERY/CELL,” issued Jan. 28, 2014; U.S. Pat. No.8,791,669, titled “METHOD AND CIRCUITRY TO ADAPTIVELY CHARGE ABATTERY/CELL,” issued Jul. 24, 2014; U.S. Pat. No. 9,121,910, titled“METHOD AND CIRCUITRY TO ADAPTIVELY CHARGE A BATTERY/CELL USING THESTATE OF HEALTH THEREOF,” issued Sep. 1, 2015; U.S. Pat. No. 9,142,994,titled “METHOD AND CIRCUITRY TO ADAPTIVELY CHARGE A BATTERY/CELL,”issued Sep. 22, 2015; U.S. Pat. No. 9,035,623, titled “MONITOR ANDCONTROL CIRCUITRY FOR CHARGING A BATTERY/CELL, AND METHODS OF OPERATINGSAME,” issued May 19, 2015; and U.S. Pat. No. 8,907,631, titled“ADAPTIVE CHARGING TECHNIQUE AND CIRCUITRY FOR A BATTERY/CELL USINGMULTIPLE CHARGING CIRCUITS AND TEMPERATURE DATE,” which issued Dec. 9,2014. Each of these patents is incorporated herein by reference in itsentirety.

In some embodiments, battery parameters used in adaptive charginginclude physical characteristics of the battery that are reflective of abattery's response in certain frequency or time domains, such as thoseassociated with metal ion diffusion in the battery's electrolyte orelectrode (anode or cathode), and/or reaction rates at the battery'sanode or cathode. Such characteristics may be derived usingelectrochemical impedance spectroscopy or related techniques.

To illustrate an example of adaptive charging, FIG. 2 shows how acharging process can reduce or minimize the “overshoot” or “undershoot”of the decay of the terminal voltage of the battery by adjusting theamplitude and pulse width of a discharge pulse. When a charge processprovides an “overshoot” of the decay of the terminal voltage of thebattery relative to partial equilibrium (see discharge pulse A), thecharging circuitry may adjust the characteristics of the discharge pulseby, e.g., increasing the amount of charge removed by the dischargepulse. For example, by increasing the amplitude and/or pulse width ofthe discharge pulse, the overshoot may be corrected. When a chargeprocess results in an “undershoot” of the decay of the terminal voltageof the battery relative to partial equilibrium (see discharge pulse C),charging circuitry may decrease the amount of charge removed by thedischarge pulse (for example, via decreasing the amplitude and/or pulsewidth of the discharge pulse). As such, the control circuitry may adjustthe characteristics of one or more subsequent discharge pulses (forexample, the amplitude, pulse width, and/or pulse shape) to control oradjust rate, shape and/or characteristics of the decay of the terminalvoltage of the battery. Other examples of charge process modification toaccomplish adaptive charging include modifying the rate or amount ofcharge injected to the battery during charging. In general, in one classof adaptive charging techniques, the charge process changes theamplitude and/or duration of one or more discharge pulses to stimulate adesired response in the partial relaxation time. Examples of adjustableparameters of discharge pulses are illustrated in FIGS. 8b and 8 c.

FIGS. 3a-3d present example waveforms of charge signals. A charging orrecharging sequence, operation, or cycle may include charging signals(which, in total, inject or apply charge into the battery) anddischarging signals (which, in total, remove charge from the battery).Charging signals may decrease according to a predetermined rate and/orpattern (for example, asymptotically, linearly or quadraticaly) as,e.g., the terminal voltage of the battery increases during a charging orrecharging sequence, operation, or cycle (see, e.g., FIGS. 3b and 3d ).In some cases, a pulse charging sequence or operation may include aconstant voltage (CV) phase after a period of pulse charging and/or uponcharging the battery/cell to a predetermined state of charge. In someembodiments, the period prior to the CV phase involves controllingcurrent delivered to the battery. In some cases, this phase is nominallya constant current (CC) phase— although pulses may be superimposed—or acurrent step phase.

FIGS. 4a-4e illustrate charge and/or discharge packets of the chargingand discharging signals (which are illustrated in FIGS. 3a-3d ), wheresuch charge and discharge packets may include one or more charge pulsesand one or more discharge pulses. In some embodiments, a charge signalof FIGS. 3a-3d includes a plurality of packets (for example, about 100to about 50,000 packets) and, in some embodiments, each packet mayinclude a plurality of charge pulses, discharge pulses, and restperiods. More generally, a charge packet includes one or more changes incharging current or other charging parameter. In some cases, thechange(s) contained in a charge packet include an edge in the chargecurrent. When pulses are used, they may be of any shape—for example,pulses may be, rectangular, triangular, sinusoidal, or square. In someembodiments, charge and/or discharge pulses of the packet may include atemporal duration of between about 1 ms to about 2000 ms, and preferablyless than 1000 ms. Note that the concept of a “packet” is not essentialto characterize a charging process. Some pulse charge processes may beamply described as a series of charge (and optionally discharge) pulsesor steps. Step charging protocols are within the purview of thisdisclosure. Adaptive charging may involve modifying the amplitude,duration, and/or other characteristic of one or more steps in a stepcharging process.

FIG. 4f illustrates an example of a charge packet having a charge pulsethat includes a charging period (T_(charge)) followed by a rest period(Trent) where the period of the charge packet is identified asT_(packet).

FIG. 4g illustrates an example of a charge packet having a charge pulse(which injects charge into the battery) and a discharge pulse (whichremoves charge from the battery) where the charge pulse includes acharging period (T_(charge)) and the discharge pulse includes adischarging period (T_(discharge)). As depicted, an intermediate restperiod (T_(inter)) is disposed between the charge and discharge pulses,and a rest period (Tress) is disposed after the discharge pulse andbefore the next packet.

Discharge signals may be employed to reduce the time period for thebattery terminal voltage to return to equilibrium. In this regard, thedischarge period may remove excess charge that might otherwisecontribute to degradation mechanisms such as the thickening of thesolid-electrolyte interface (SEI) layer or metallic plating of lithium.The difference between the electrical charge added to the cell during acharging period and the electrical charge removed from the cell during adischarge period determines a net total electrical charge added to thecell in one period. This net total electrical charge divided by theperiod may determine a net effective charging current.

There are numerous combinations and permutations involving the amount ofelectrical charge added to the battery during the charge signal and theamount of charge removed during the discharge signal. All permutationsare intended to fall within the scope of the present disclosure. Forexample, each permutation may result in a different rate, shape and/orcharacteristics of the decay of the terminal voltage of the battery.Moreover, within each permutation, there exists a large number ofsub-permutations that i) combine the characteristics of a charge signal(for example, the duration, shape and/or amplitude of the chargesignal), the product of which determines the amount of electrical chargeadded to the cell; and ii) combine the characteristics of a dischargesignal (for example, the duration, shape and/or amplitude of a dischargesignal), the product of which determines the amount of electrical chargeremoved from the cell; and iii) the length of time of the rest period.The characteristics of a charge signal may differ from thecharacteristics of a discharge signal. That is, one or more of theduration, shape and/or amplitude of the charge signal may differ fromone or more of the duration, shape and/or amplitude of the dischargesignal.

Some or all of the characteristics of the charge and discharge pulses orsteps may be programmable and/or controllable. For example, the pulse orstep amplitude, width/duration, and shape may be adjusted. In otherexamples, the amplitude of the positive and/or negative pulses may varywithin the packet, the duration and/or timing of the rest periods mayvary within the packet, and/or pulses may be equally or unequally spacedwithin the packet. The combination of charging pulses, dischargingpulses and rest periods may be repetitive, thereby forming a packet thatmay be repeated.

FIG. 5a illustrates current and voltage of a battery as a function oftime illustrating the conventional charging method known asconstant-current, constant-voltage (CCCV). When charging a rechargeablebattery (e.g., a lithium-ion type rechargeable battery) using CCCV, thecharging sequence includes a constant-current (CC) charging mode untilthe terminal voltage of the battery/cell is at about a maximum amplitude(for example, about 4.2V to 4.5V for certain lithium-ion typerechargeable batteries) at which point the charging sequence changesfrom the constant-current charging mode to a constant-voltage (CV)charging mode. In the CV mode, a constant voltage is applied to theterminals of the battery. Generally when charging a rechargeable batteryusing the CCCV technique, the charging circuitry changes from the CCcharging mode to the CV charging mode when the state of charge (SOC) ofthe battery is at, e.g., about 60-80%, although in some embodiments, asdescribed herein, a charging circuitry does not enter a CV charging modeuntil the battery charge is greater than about 90% SOC or greater thanabout 95% SOC. Adaptive charging may be employed to adjust the CC and/orCV portions of a CCCV charging process. Adaptive charging may also beemployed to adjust the transition from the CC to the CV portion of theprocess.

FIG. 5b illustrates current and voltage of a battery as a function oftime when charged by a step-charging technique. FIG. 5b shows a singleexample of a step charging technique. A step-charging process of arechargeable battery (e.g., a lithium-ion type rechargeable battery)employs a multiple step constant-current (CC) charging mode until, e.g.,the terminal voltage of the battery is at about a maximum amplitude (forexample, about 4.2V to 4.5V for certain lithium-ion type rechargeablebatteries) at which point the charging sequence changes from theconstant-current charging mode to a constant-voltage (CV) charging mode.As with the CCCV technique depicted in FIG. 5a , a constant voltage isapplied to the terminals of the battery while in the CV mode. And aswith the technique depicted in FIG. 5a , adaptive charging may beemployed to adjust the CC (including individual steps, amplitude,duration) portion, the CV portion, and/or the transition from the CC tothe CV portion of the process.

Battery Models and Their Use A. Battery Model Overview

Aspects of this disclosure pertain to models or similar tools forcharacterizing or classifying a battery and/or a battery'scharacteristics (e.g., charge characteristics) at various points in thebattery's life, some or all of which may be when the battery is inservice, as for example when the battery is installed in an electronicdevice such as a phone, an automobile, etc. In certain embodiments,models are developed or refined using information about a batterycollected while the battery is in service. Regardless of how a model isgenerated and/or updated, it may classify a battery in a way thatidentifies different charge process regimes or characteristics of thebattery.

A simple pictorial example of a two-dimensional battery model isrepresented in FIG. 5c . As shown, the model classifies charge processparameters for a particular battery—in this particular case, values ofstate of charge and charge current. Using these charge parameters, themodel classifies the charging process according to a particular state:safe, safe and slow, potentially unsafe, and known unsafe, therebydefining inter-relationships between the parameters under consideration(in this simple example, state of charge and charging current).Understand that while the plot of FIG. 5c shows charge current and stateof charge as charge process parameters, often a model will considerother and/or additional charge process parameters and/or operatingconditions such as temperature, terminal voltage (provided in isolationor as a response to a stimulus such as an applied current edge), batteryage/health, material properties, sampling periods to obtain therequisite information, durations of measurement, etc., all of which mayconstitute independent axes in a multi-dimensional model. At the core ofthe multi-dimensional models are relationships that connect theindependent parameters (and axes) to each other. These relationshipsthen determine the optimal charging and operation of a battery.

In some cases, a battery's charge process parameters may be visualizedin a battery parameter space having a number of dimensions associatedwith these parameters. Thus, while FIG. 5c shows two dimensions ofbattery charge process parameter space, other examples have three ormore such dimensions. The number of battery charge process parametersincluded in a model (and hence a multidimensional space considered bythe model) depends on the ability of chosen parameters to accuratelyand/or safely classify a battery or serve another requirement. Incertain embodiments, the model employs at least two battery chargeparameters, or at least about five battery charge parameters. Regardlessof the number of dimensions, each set of battery charging processparameter values, alone or in combination with battery type information,represents a point in the multidimensional parameter space.

As used herein, the term battery charge process parameters or justbattery charge parameters indicates information about a battery,sometimes including information about a battery's charge conditions,(e.g., state of charge and current magnitude) that may be input to amodel, while the term battery charge process characteristics or justbattery charge characteristics indicates a conclusion or predictionabout the results or appropriateness of the battery when subjected toparticular battery charge parameters. Examples of battery charge processcharacteristics include safe operating conditions, potentially unsafeoperating conditions, and known unsafe operating conditions. Distinctbattery charge process characteristics may occupy different regions orregimes in a multidimensional space representing battery charge processparameters. In other words, the space is divided into regions, eachassociated with a different classification or characteristic of a givenbattery. The boundaries between these regions may be sharp or graded(i.e., the transition between a safe to a potentially safe chargeprocess region may occur over distance in parameter space). See thedistinct regions in FIG. 5c . A battery model classifies a battery andassociated charge process parameters into one of theregimes/characteristics.

Alternatively, or in addition, to simply classifying a battery byposition in multidimensional battery parameter space, a battery modelmay produce a score based on battery charge process parameter values,optionally with weights applied to individual parameter values. Forexample, the score may be a weighted summation of selected individualbattery charge process parameters. In certain embodiments, the weightscan be computed from statistical analyses of the properties ofpreviously tested batteries. Other functions of the battery chargeprocess parameters, such as non-linear functions, may be used to obtaina score.

In some embodiments, principal component analysis or a similar techniquefor reducing dimensionality is applied to a data set containing chargeprocess parameter values for batteries and their associated chargingprocedures. The principal components of the dataset define vectors ofmaximum variation through the multidimensional parameter space. Theprincipal components may be used in a reduced dimension batteryparameter space. In some cases, a battery model is trained or otherwisedesigned to use parameter values presented in terms of principalcomponents.

In certain embodiments, separate models are provided for differentbatteries. This reflects the fact that individual batteries frequentlyhave different characteristics, which result from different designs,manufacturing, handling, and/or use in service. In some implementations,multiple batteries of the same type (e.g., the same size, format,chemistry, manufacture, and batch) may use the same model, at leastinitially. Over time, the models for individual ones of these batteriesof the same type may evolve or develop into different models to accountfor distinct observed properties, which may result from initiallyunknown differences or from use patterns differences. As should beapparent from this example, models can change over time, and the changescan be dictated by observed changes in a battery's response toparticular stimuli or other conditions. Some examples of batteryresponses are described below with respect to time domain and frequencydomain battery information. For example, a battery model may employelectrochemical impedance spectroscopy (EIS) or EIS-like information togenerate or refine or train a model.

In certain embodiments, the battery is evaluated in situ using a model.That is, the battery need not be removed from its electronic device inorder to be classified by the model. Collection of battery parametervalues and application to a battery model may be conducted in a way thatis unobtrusive, e.g., during charging and in a way that does notsignificantly slow or modify the charging. In some implementations orsome use patterns, the model may conduct its evaluations without beingnoticed by the user of the device powered by the battery.

The battery charge process characteristics provided by a model mayinform decisions about future performance of battery and/or actions tobe taken to address potential safety hazards, performance degradation,charging procedures, etc. For example, a particular model for aparticular battery may indicate that the battery can or should becharged with a current of greater than 0.5 A when the battery's state ofcharge is 40% at a given temperature. The same model may indicate thatthe battery can be comfortably and appropriately charged with a currentof about 0.6 A when the battery's state of charge is 80% at the sametemperature. Still further, the model may indicate that the batterydefinitely should not be charged with a current of greater than 0.5 Awhen the battery's state of charge is 90% also at the same temperature.In certain embodiments, the battery charge characteristics are used toadapt charge process parameters (e.g., as with adaptive chargingdescribed herein).

B. Input and Output Variables

As explained, a battery model may receive as inputs various batterycharge process parameters. Examples of classes of these parametersinclude the following: (a) applied current characteristics (e.g.,magnitude or shape such as pulse, edge, or step characteristics), (b)measured voltage across the battery terminals (e.g., as a function oftime after the applied current pulse(s) or at fixed times after thecurrent pulse(s)) (measured at various times after the stimulus or inresponse to various stimulus frequencies), (c) state of charge(determined by open circuit voltage, coulombs passed, etc.), (d)temperature (measured via a temperature sensor and optionally providedas a function of time after the applied current pulse or at fixed timesafter the current pulse), (e) battery age (cycle count, days in service,etc.), (f) previously generated output variables and/or battery state ofhealth, (g) sampling frequencies of the current and/or voltage values,(h) duration of the sampling and measurement period (sampling frequencyand duration point to different physical and chemical processes withinthe battery), (i) design values of the battery obtained either directlyfrom the manufacturer or through physical dissection of the battery(e.g., material thicknesses, dimensions, properties of the electrolyte,known temperature dependences of such material properties), and thelike.

In certain embodiments, battery models are configured to receiveparameter values for both current applied to the battery and voltageacross the battery terminals. In some cases, battery models use, inaddition, some combination of parameters of the types (c)-(f) listedabove. In certain embodiments, battery models use the battery's appliedand/or measured current at multiple different states of charge; in otherwords, at various states of charge, encountered over the course of asingle charge process or over multiple charge processes. In certainembodiments, battery models use (i) the charge current, (ii) associatedterminal voltage, and (iii) state of charge are provided as inputs tothe model. Note that the charge current used in models may be, e.g., aninstantaneous charge current or an average charge current. In somecases, an instantaneous charge current is obtained over a period ofmilliseconds to tens of seconds. Regardless of what battery chargeprocess parameter values are input to the model, the model classifiesthe charge process having these parameter values. Note that the currentand voltage values, as well as certain other charge process parameters,may be provided in a particular time domain or frequency domain, as isfurther explained below.

To generate values of certain of these input variables, a battery systemmay apply a stimulus, which may be a current pulse applied at aspecified state of charge. In response to the applied stimulus, thesystem measures the terminal voltage, and optionally one or more otherparameter values such as the temperature of the battery.

The applied current is not necessarily a current pulse; in variousembodiments it is some form of an edge, which is a change in themagnitude of applied current. From the perspective of signal theory, anedge contains harmonic frequencies, which may be considered whenevaluating a battery's response to the applied current edge. Thefundamental and harmonic frequencies may be the primary mechanism tostimulate the battery's response. Note that the magnitude of currentedge need not go to zero Amps to provide an edge; it merely has tochange in value and in time. Further, the edge need not be vertical, asin the case of an edge of a triangular wave. The rate at which the edgechanges should contain a sufficient frequency bandwidth to stimulate thefrequencies of interest within the battery. The terminal voltage and/orother parameter may be measured at various times during or afterapplication of the current edge. Alternatively, in some circumstances,the stimulus itself may be the terminal voltage instead of the terminalcurrent.

The model output classifies a battery under a set of conditions. Themodel may do this for conditions at the time of the measurement or atsome other time such as a future time when exposed to a hypothetical setof conditions (e.g., an anticipated future applied current magnitude ata particular state of charge and temperature).

In certain embodiments, the classification provided by a battery modelallows the charging system to suggest or implement a change in a chargecondition (e.g., an increased or decreased instantaneous or averagecurrent). In certain embodiments, the classification allows the controlsystem associated with the battery or an electronic device in which thebattery is installed to determine whether the battery is operating in apotentially unsafe mode and should be flagged for further observation orhave its operation terminated. In certain embodiments, theclassification allows the system to determine that the battery is inimminent danger of failure and/or represents a serious safety concern.In such cases, a system may prevent further charging and/or discharginguntil the battery has been removed or replaced from the device.

Returning to FIG. 5c , a classification plot 521 represents a simplifiedpictorial example of a battery model for a given battery or a family ofbatteries. The plot 521 provides four discrete regions that representfour different battery charge process characteristics. As shown, theseare a safe but slow charging region 523, a generally safe operatingregion 525, a potentially unsafe operating region 527, and known unsafeoperating region 529. If the charging process operates in the safe butslow charging region 523, the battery is unlikely to be damaged ordestroyed, but it might be charged more rapidly without problem. Inother words, while the battery is safely charged in region 523, thecharging process logic might determine that the battery should becharged faster, possibly to a level within the region 525. As shown,region 525 lies above (has a higher charging current) than region 523,but it does not extend into high states of charge. In other words, acharging process that operates at both a high state of charge and a highcharge current is deemed unsafe by the battery model. Generally,batteries operating in region 525 are considered to be safely charged atan adequately fast charge rate. It is readily possible to picture amulti-dimensional version of FIG. 5c where additional parameters (oraxes) are added, such as temperature, health and/or aging, operatingcondition, etc.

As shown, the model characterizes charging processes that use relativelyhigh charging currents at high states of charge as either potentiallyunsafe (region 527) or known to be unsafe (529). A known unsafeoperating region may be one where a failure of the battery may lead indue time to a fire or explosion. For example, a buildup of metalliclithium may cause dendritic filaments that can cause an internalelectric short-circuit thereby leading to a rapid discharge of thebattery and a likely fire. A potentially unsafe region is one where therisk of failure is elevated, but where failure may or may not involvefire or explosion. If a device's charging logic determines that abattery is operating in one of these regions or will soon be operatingin one of them, it may adjust its charging parameters to stay out ofthese regions.

In some embodiments, the charging logic attempts to operate close to aboundary 531 between safe region 525 and potentially unsafe operatingregion 527. Of course, the logic will attempt to stay on the safe sideof boundary 531, but this of course requires that the model accuratelydefines the boundary. Further, the boundary can vary frombattery-to-battery, or even at different evaluation times for a givenbattery.

These boundaries or thresholds between different regions may, in somecases, depend on previous or on-going measurements of battery propertiessuch as voltage measured in response to particular stimuli. For example,a current charge threshold (e.g., for boundary 531) may be relaxed ifthere is a detected gradual (or abrupt) change in the battery's responseto particular stimuli, which response indicates that operating at highercurrents does not pose a safety threat. In certain embodiments, theboundary determination is made (and periodically updated) using anoptimization scheme that takes, e.g., various EIS measurements as inputsand determines how they relate to a defined specification (e.g., chargetime, cycle life, health and aging progression, etc.). The boundarydetermination or update may iterate this process using present andhistorical data and inputs, if necessary, to adjust the model, whichallows for updating an optimal charge process configuration.

As indicated, the model illustrated in FIG. 5c provides just one ofexample of many possible model structures. The parameters considered todefine the space in which a charge process for a battery is classifiedcan include, as examples, any one or more of the following: state ofcharge, charge current (average, peak, etc.), voltage responses (whichmay be provided at various time or frequency regimes), etc.

C. Developing the Model

To develop a battery model, a group of batteries such as those of aparticular battery type provided by a particular vendor is analyzed forsuch factors as the state of health of the battery under variousconditions, the failure of the battery, and safety issues. Safety issuesinclude such issues as plating of metal onto the anode during charge andconsequent formation of conductive dendrites, loss of batteryelectrolyte, swelling, and fire or explosion of the battery.

The computational system or individual(s) charged with developing themodel analyzes some or all of the above-identified input variables forpatterns or trends that are reflected in a computational model thatclassifies batteries based on values of the input variables (chargeprocess parameters). Information about each battery including batterycharge process parameters and associated battery charge processcharacteristics/classifications may collectively serve as a training setfor developing the battery model.

Batteries chosen for study in developing a model may be selected basedon various criteria. As mentioned, they may all be of the same type, butin some cases other criteria are used. For example, the batteries may beselected based on differences in how a battery operates, which may bedetermined based on physical know-how. Thus, in some cases, an expertpossessing such knowledge considers model empirical parameters that maybe due to, e.g., manufacturing variability and factors this associationinto choosing batteries for developing a battery model. In other cases,a computational system selects batteries to be analyzed for developing abattery model.

The mechanics of developing a battery model can take various forms. Inone approach, one or more experts analyze battery data and makedeterminations of what are safe and unsafe regions of battery chargingprocess parameter space. Other methods include various computationalmodelling and machine learning techniques that can identify patterns inthe input variables and associated conditions of batteries (e.g., normalor expected behavior, unexpected degradation, potentially dangerous tooperate, and imminent failure or imminent safety issue).

A battery model may take various forms. Examples include CART(Classification and Regression Trees), random forest models, neuralnetwork, regression model, support vector machines, probabilities models(e.g., log likelihood), look up tables, and other models andrelationships known to those of skill in the art.

D. Using the Model

A model may be executed at any of various locations. In certainembodiments, logic for executing the battery model resides entirely onthe device or the device charger (e.g., with a battery pack or aprocessor used by the device for other purposes). In certainembodiments, logic for executing the battery model resides at a remotelocation (e.g., a cloud or a server under the control the batterymanufacturer, the device manufacturer, or the batterycharging/monitoring system provider). In certain embodiments, logic forexecuting the battery model is distributed between local and remoteresources.

As explained, in some implementations, battery control logic may monitoror otherwise determine parameters associated with a charging process.Some of these may be used as battery charging process parameters, e.g.,inputs to a battery model. These parameters may be provided directly orindirectly from the measurement circuitry. See e.g., FIG. 1. Raw batterymeasurements taken by the measurement circuitry include but are notlimited to temperature, voltage, current, charge passed, and time fromor between events. In some embodiments, raw battery measurements arepassed to the control circuitry, which may employ logic to determineparameters such as SOC, SOH, overpotential, and PRT. Depending on thedesign of the battery model, any raw or derived measurements andparameters may be used by battery models. As an example, measurementssuch as a battery's SOC are made directly by measurement circuitry andpassed to a battery model. Raw and/or derived parameters may be storedlocally or on a remote device and provided, at an appropriate time, tothe battery model for analysis and ultimately to provide a batterycharge process classification. The analyzed present and/or historicaldata and/or battery charge process classification may be fed back intothe battery control logic to allow for, e.g., adaptive charging, safetyalerts, etc.

In some implementations, battery models are trained or further refinedover time, such as when service data from one or more batteries iscollected, to improve the performance of the models. In some cases,multiple batteries, such as batteries on phones, can provide informationthat serves as data points for further training a model. For example,when a battery experiences failure, as detected by the device or by auser, the data leading up to or otherwise associated with the failurecan be used to improve the accuracy of a battery model. This approachmay, e.g., identify rare manufacturing defects.

The model results or outputs may be treated or used in various ways. Inone approach, model results/outputs broadly classify a battery asbehaving (a) as expected for a normal battery of similar age, (b) in away suggesting a premature failure risk, or (c) in a way that poses asafety risk. If the battery is behaving as expected, the batterycharging system may adapt the charge protocol to permit faster charging.If the battery is behaving in a way suggesting that it might failprematurely, the battery charging system or other logic may send analert to the user, and/or the manufacturer, and/or adapt the chargingprotocol to extend the battery life. If an alert is sent, it mighttrigger a warranty clause for the device and/or battery, and/or it mightsuggest early replacement of the battery. If the battery is behaving ina way that poses a safety risk, the responsible system may shut down thedevice and send a warning to immediately replace the battery or deviceor take some other precaution.

Characterizing Battery Physical Phenomena

a. Time Regimes and Battery Phenomena

Battery performance is affected by various phenomena, each having anassociated response time to events that can occur during batterycharging. While not an exhaustive list, three classes of phenomena willbe used as examples: (1) lithium ion transport in electrolyte, (2)reaction kinetics occurring at the electrode surface (often the anode),and (3) lithium ion diffusion within the solid matrix of an electrode(anode or cathode). Understand that while this disclosure frequentlymakes reference to lithium ions, the disclosed concepts extend tobattery systems that employ other types of current carrying ions such assodium ions.

Lithium-ion transport in a battery's electrolyte, which may bequiescent, is typically caused by some combination of migration(movement of charged species in an electric field) and diffusion(movement driven by a concentration gradient) in the electrolyte. Thistransport is a relatively fast process and is reflected in data obtained(i) with a high-frequency stimulus (e.g., a high frequency currentsignal applied in electrochemical impedance spectroscopy) and/or (ii) atshort times after a stimulus is applied. The response time of lithiumions in a battery electrolyte is typically on the order of a few to tensof milliseconds, although it may be slower in some types ofelectrolytes, particularly some solid state electrolytes, in which casethe response time is typically on the order of up to about 1 to 5seconds. Transport of metal ions in a liquid battery electrolyte may bereflected in battery response characteristics such as partial relaxationtime (see e.g., FIGS. 8a-c ).

Kinetics of reactions taking place at the interface of the electrode(s)in a battery are governed by various factors. In the anode or negativeelectrode (during charging), the changes in the reaction kinetics canreflect the growth of an SEI layer and/or the nature of electrochemicalreactions at the interface. These phenomena are noticeable in dataacquired in response to an intermediate frequency stimulus in the caseof electrochemical impedance spectroscopy. The response time of aninterfacial reaction in a battery is typically on the order of a fewmilliseconds and is typically longer than the response time of iontransport in the electrolyte. Interfacial reactions at battery'selectrode surface (e.g., anode surface) may be reflected in batteryresponse characteristics such as partial relaxation time, overpotential,and CPV.

Transport of lithium ions in the solid electrode material such as carbonor silicon or metal oxide may be reflected by the diffusion of lithiumions in the solid matrix of the electrode. Characterization of thisphenomenon can be obtained using relatively low frequency stimulation.The response time of diffusion of metal ions in an anode active material(e.g., lithium ions in graphite) of a battery is typically on the orderof few to tens of seconds and is typically longer than the response timeof reaction kinetics at the electrolyte-electrode interface. Transportof metal ions in the solid particles of the electrode may be reflectedin battery response characteristics such as charge pulse voltage (CPV)and relaxation time.

Note that a response time in a battery may be measured from a step orpulse and may be characterized by a time constant. In this context, atime constant may be understood to represent the elapsed time requiredfor the battery response to decay to a near-equilibrium value if thesystem had continued to decay at the initial rate. In the case of anexponential decay, the response will have actually decreased in value toin this time (from a step decrease). In an increasing exponentialsystem, the time constant is the time for the battery's response toreach its final (asymptotic) value (from a step increase). For certainbattery processes, the rate of decay is close to an exponential decay,but it is not actually an exponential decay.

The time constant for full relaxation is on the order of hundreds ofmilliseconds to seconds. The time constant for CPV is similar. The timeconstant for partial relaxation is on the order of tens of milliseconds.As explained, each reflect a different process within the battery. Eachis also stimulated by a “pulse” or “edge” of sufficient bandwidth (i.e.,contains enough harmonics). Regarding measurement of relaxation timeversus partial relaxation time, shorter measurement duration (afterapplication of the current edge or other stimulus) and faster samplingtend toward partial relaxation time, while longer measurement durationand slower sampling tend toward full relaxation time. In certainembodiments, although this is not required, relaxation time is measuredwith a positive current step or pulse, and partial relaxation time ismeasured with a negative current step or pulse.

a. Electrochemical Impedance Spectroscopy

Electrochemical impedance spectroscopy is conventionally performed byapplying a small excitation signal, typically an AC potential, to theelectrochemical cell and measuring the resulting current through thecell. Assuming that a sinusoidal excitation potential is applied, theresponse is a sinusoidal current signal. By measuring the amplitude ofthe response and the phase difference between the excitation andresponse, both as a function of applied frequency, a test system canprovide information about the mechanisms or performance of theelectrochemical cell. This information includes or is influenced by theresponse times discussed above.

Approaches to analyzing electrochemical impedance spectroscopy dataoften model electrochemical cells using equivalent circuit elements suchas resistors and capacitors. Charge transfer, reaction kinetics,diffusion, and other electrochemical phenomena can be represented ascircuit elements, and a battery can be represented as one or morecircuits having such elements arranged in series or parallel or acombination of series and parallel. Some models use empirically derivedelements as alternatives to or partial substitutes for physical modelelements (e.g., physical circuit elements such as resistors, capacitors,and combinations thereof).

Some electrochemical impedance spectroscopy tools attempt to find amodel whose calculated impedance matches the measured impedance of abattery under consideration. When model parameters provide goodagreement with observed electrochemical impedance spectroscopy results,the model parameters can provide good physical insight into theoperation of a battery. Electrochemical impedance spectroscopy (EIS) isfurther described in the book “Electrochemical Impedance Spectroscopyand its Applications,” by A. Lasia, (2014), Springer, published bySpringer, which is incorporated herein by reference in its entirety.

In certain embodiments, an EIS applied stimulus is provided bysuperimposing a known signal of a single frequency and scanning thefrequency. In some implementations, EIS applied stimulus is provided inthe form of current pulses at various frequencies where a particulartype of battery phenomenon can be characterized. In certain embodiments,a battery is probed, in situ, by applying a signal of various harmonicfrequencies during battery charging or during some other time. As withconventional EIS, the applied pulses may include a wide range offrequencies, which may be provided over a continuous or near continuousrange. Alternatively, discrete ranges of frequency can be applied. Inall cases, the response of the battery is monitored. Together thevoltage and current values provide impedance information used tocharacterize the battery. In some scenarios, the stimulus is current andthe measured response voltage. However, the reverse can be employed.

As mentioned, lithium-ion transport in an electrolyte is a relativelyfast process, which means that it is reflected in high-frequency datadetermined with electrochemical impedance spectroscopy. Examples of suchfrequencies are in the range of about 100 Hz to 2 kHz, or equivalentlyshort durations of time, e.g., about 10 ms to 100 ms. Kinetics ofreactions taking place at the interface of the electrode are noticeablein data acquired at intermediate frequencies, e.g., frequencies in therange of about 10 Hz to 0.5 kHz, or equivalently short durations oftime, e.g., about 2 ms to 100 ms. Diffusion of lithium ions in the solidanode material such as carbon or silicon can be characterized atrelatively low excitation frequencies, e.g., frequencies in the range ofabout 1 mHz to 1 Hz, or equivalently longer durations of time, e.g.,about 1 second to 1,000 seconds.

Data collected over a range of frequencies in electrochemical impedancespectroscopy is commonly presented in a Bode plot or a Nyquist plot; thelatter shows the value of the imaginary component of impedance as afunction of the real component of impedance. FIG. 6 shows an exampleNyquist plot for a lithium ion battery (adapted from Comsol Blog, TommyZavalis, July 2015,comsol.com/blogs/studying-impedance-to-analyze-the-li-ion-battery-with-an-app/).As can be seen, the plot includes distinct portions that are associatedwith the three relevant battery physical-chemical phenomena. The curvesin the mid and high-frequency ranges may reflect ion transport in aliquid electrolyte, charging of double layers on the materials withinthe electrode, and resistances of the electrode materials and resistivefilms. The mid-frequency curve reflects the rate of a charge transferreaction. The lower frequencies curve or tail reflects ionic diffusionwithin the active electrode materials. The location and size of the tailmay be controlled by the diffusion constants and the particle size forthe electrode material. Each such zone reflects physical and materialproperties underlying the relevant physical-chemical phenomena. As abattery ages or otherwise changes, the impedance information in one ormore of these regimes correspondingly changes.

The impedance measurements can be used with a battery model tocharacterize the battery phenomena. In certain embodiments, one may varymodel parameters to determine what features of a battery affect theimpedance at a particular frequency or particular frequencies.Alternatively, one can fit the model to experimental impedance datathrough an optimization procedure and examine the properties.

In certain embodiments, a battery system is designed or configured toconduct EIS in situ, i.e., while the battery is installed in a devicesuch as a consumer electronics device (phone, camera, etc.) or a vehicle(e.g., a car, truck, airplane, boat, or motorcycle). In certainembodiments, the system conducts EIS at times when battery is beingcharged and/or is not being used (e.g., when the battery is not beingdischarged; typically when an end user is not using the device). Thesystem may conduct EIS by applying current pulses at differentfrequencies and measuring the resulting terminal voltage amplitude andphase. It may scan an entire spectrum of frequencies, from mHz to kHz,or a subset. In some implementations, the system applies voltage pulsesand measures the battery's current response (at one or both of thebattery's terminals). The battery system may be designed or configuredto conduct EIS in a way that captures information spanning a range ofbattery conditions: e.g., the system conducts EIS at different states ofcharge, different temperatures, etc.

The system may be configured to analyze EIS results (e.g., magnitude andphase of voltage) as a function of at least the applied currentfrequency and magnitude. It may also analyze these results in terms ofone or more of the following battery parameters: temperature, state ofcharge, and health or age (e.g., number of charge cycles, days inservice, etc.). From the EIS results, the system may determine whether abattery is behaving (a) as expected for a normal battery of similar age,(b) in a way suggesting a premature degradation or failure risk, or (c)in a way that poses a safety risk. For example, a measurement of theionic diffusion in an electrode at a particular SOC and/or temperatureis reflective of the integrity of the electrode material and batterydesign. Mechanical stress in the electrode or fracture of the electrodematerial grains may lead to slower detected diffusion as observed fromlow frequency information. Similarly, thickening of thesolid-electrolyte-interface (SEI) layer may be reflected in slowerdetected diffusion as well as worsening surface properties measured asobserved from mid frequency information. If the battery is behaving asexpected, the system may consider adapting the charging protocol topermit faster charging. If the battery is behaving in a way suggestingthat it might fail prematurely, the system may send an alert to the userand/or the manufacture. If such alert is sent, it might trigger awarranty clause for the device and/or battery, and/or it might suggestearly replacement of the battery. Alternatively or in addition, if thebattery is behaving in a way suggesting that it might fail prematurely,the system may adapt the charging protocol to extend the battery life.If the battery is behaving in a way that poses a safety risk, the systemmight shut down the device and send a warning to immediately replace thebattery or device or take some other precaution. A safety risk mightarise if the system detects significant plating of lithium, a hightemperature excursion, significant electrolyte degradation, or the like.

FIG. 7a presents an example process flow for implementing an in situfrequency domain analysis of a battery. In the depicted embodiment, oneor more stimulus frequencies are applied to a battery and the battery'sresponse is measured at the one or more frequencies. The resultinginformation is analyzed to provide frequency-specific impedance datathat may be used to ascertain one or more physical phenomena in thebattery (e.g., ion transport and/or interfacial reactions). Thefrequency-specific impedance information may be used as feedback for anadaptive charging procedure and/or for issuing notifications, warning,or taking actions to avoid or mitigate potential safety issues.

As shown in FIG. 7a , a process 701 begins with an operation 703involving applying an in situ frequency-specific stimulus (e.g., adefined current or voltage) to a battery. Examples of frequency-specificstimuli are described elsewhere herein. For instance, an oscillatingcurrent signal may be scanned over a range of frequencies. In someimplementations, the stimulus is provided as a range or one or morediscrete frequencies within the range of about 1 mHz to 5 kHz. While thebattery is exposed to the frequency-specific stimulus, itsfrequency-specific response is measured or monitored in situ. Seeoperation 705. Examples of frequency-specific measurements are describedelsewhere herein. Often the measurements determine the amplitude of theresponse and the phase of the response with respect to the appliedstimulus. For example, the phase and amplitude of a battery's voltagemay be measured in response to an oscillating current stimulus.

With data from both the stimulus and response, the process may analyzethe battery's frequency response and, optionally, determine impedance atmultiple frequencies. See operation 707. Thus, in some cases, theprocess determines an impedance spectrum of the battery. Of course, thereal and imaginary parts of impedance and/or the associated amplitudeand phase of impedance may be considered. Such information may bedetermined and/or used in the same manner as EIS data. For example, asexplained, the impedance data may be used to ascertain physicalconditions within a battery such as transport and reaction phenomena.The stimulus may be either current or voltage, with the correspondingresponses being voltage or current.

From the analysis of the frequency response, the process may determinewhether to issue a notification and/or modify treatment of the battery.See operation 709. If the process determines that it should issue suchnotification or modify such treatment, it may issue an appropriatenotification and/or modify treatment of the battery (e.g., modify acharge process). See operation 711. As indicated, modifying thetreatment may entail an adaptive charging operation.

As illustrated in FIG. 7a , the stimulus of the battery may take place“in situ,” which indicates that the operation takes place while thebattery is in a device that it powers. For example, the operation maytake place while the battery is being charged, discharged, or sittingidle in the device. Note, however, the processes described herein arenot limited to in situ processes; in some cases, the process isperformed with the battery removed from its device.

The frequency of a stimulus that affects a particular type of battery'sphysical and/or chemical phenomenon corresponds to the reciprocal of atime constant for the phenomenon. Thus, while battery information usedin embodiments of this disclosure may be obtained by frequency domainstimulus and frequency domain analysis in the same manner as EIS,similar information may be captured in the time domain and converted tothe frequency domain through, e.g., a Fourier Transform. Analysis of theresulting data may be conducted in the frequency domain as isconventional in electrochemical impedance spectroscopy. For example,rather than applying current pulses at various frequencies, a batterysystem may apply discrete current pulses (e.g., charge and dischargepulses) and measure voltage at various times after the current pulse(s).The current pulse(s) and resulting voltage variations can be decomposedinto its various frequency (or harmonic) components that constitute thepulse(s). With this information, and the voltage response at varioustimes after the pulse, the system can determine the batterycharacteristics associated with stimuli at different frequencies.

In some embodiments, an EIS-like analysis is implemented entirely in thetime domain, by applying simple current variations such as pulses (ofone or both polarities and without a frequency scan) and collectingvoltage, and optionally temperature, responses in the time domain (atvarious times after application of a current pulse). In this manner, thesystem can perform all calculations in the time domain, without evertransitioning to the frequency domain. The timescale of particular dataobtained in the time domain corresponds to the inverse values ofparticular frequencies, which correlate with different classes ofbattery physical phenomena as discussed above. When conducting batteryanalyses in the time domain, an edge of an applied current signal, whichedge might or might not begin or end at 0 Amps, serves as a stimulusthat allows measurement of response voltage across the battery terminalsat various times after the edge is applied, with those various timescorresponding to various frequencies.

FIG. 7b presents an example process flow for implementing an in situtime domain analysis, at least partially, of a battery. Thus, unlike theembodiment of FIG. 7a , the process need not scan the stimulus across arange of frequencies, need not apply the stimulus a plurality ofdiscrete frequencies, and/or need not measure a phase a response withrespect to the stimulus. However, the resulting information may beanalyzed to provide frequency-specific data that may be used toascertain one or more physical phenomena in the battery (e.g., iontransport and/or interfacial reactions). In some cases, batteryimpedance values are provided from the time-domain information. As withthe frequency domain processes, the resulting information may be used asfeedback for an adaptive charging procedure and/or for issuingnotifications, warning, or taking actions to avoid or mitigate potentialsafety issues.

As shown in FIG. 7b , a process 731 begins with an operation 733involving applying an in situ edge (e.g., a defined current or voltagepulse) to a battery. Depending on step size, slew rate, pulse width,and/or other characteristics of the edge, various pieces of informationcorresponding to various frequencies, and hence various physicalprocesses within the battery, may be elucidated. As with the process ofFIG. 7a , the process measures and/or monitors the battery's response(voltage or current) to the in situ step or edge stimulus. See operation725. As explained more fully elsewhere herein, the measurement may betaken at various times after application of the edge or other timedomain stimulus. The total duration of the measurement along with thesampling frequency and the magnitude(s) of the measured response provideinformation corresponding to various frequency-dependent impedances andhence various physical processes in the battery. Thus, a time-domainprocess such as that of FIG. 7b need not convert measurements to thefrequency domain or otherwise perform frequency-domain analyses.However, in certain embodiments, a process employing time-domainmeasurements converts the battery's response to frequency-domaininformation to provide frequency-domain analysis. See optional operation727.

Regardless of whether time-domain or frequency-domain analysis isperformed, the process may characterize the battery in terms of one ormore of its internal physical processes (e.g., transport or reactionphenomena). In some cases, as depicted in operation 729 of FIG. 7b , theprocess analyzes the battery's response in multiple time or frequencyregimes. This allows the process to consider various possible issuesthat may impact a battery's performance of safety. In certainembodiments, a time-domain battery analysis process considers thebattery's performance at one or more time points within the range ofabout 0.001 to 1000 seconds.

From the analysis of the time or frequency response, the process maydetermine whether to issue a notification and/or modify treatment of thebattery. See operation 731. If the process determines that it shouldissue such notification or modify such treatment, it may issue anappropriate notification and/or modify treatment of the battery (e.g.,modify a charge process). See operation 733. As indicated, modifying thetreatment may entail an adaptive charging operation.

Examples of Time Domain Stimulus and/or Time Domain Measurement

Stimulus

Various types of stimulus may be applied to the battery. A stimulustime-domain signal may use a charging signal or a discharging signal. Ifa charging stimulus is used, then the change in voltage in the timedomain is positive. If a discharging signal or pulse is used, then thechange in voltage in the time domain is negative. The current stimulusmay be a single edge (e.g., a step), a pulse, or other shape. Theduration and slew rate of the edge define the maximum bandwidth ofharmonic frequencies that will stimulate the battery's response. Forexample, a pulse of duration T has spectral energy at the main frequencycomponent ½T and harmonic multiples at n×½T where n=2, 3, 4, etc.

Response

Various types of signals produced by the battery in response to astimulus may be monitored or detected to provide information aboutcharacteristics of the battery. For example, voltage and/or currentresponses may be measured at one or more times after the stimulus isapplied.

In certain embodiments, voltage response to the stimulus is measured atdifferent time durations during and after the stimulus. The duration atwhich the voltage measurement is made is inversely proportional to thedesired frequency or harmonic of the stimulus. A measurement durationthat extends over a longer time is a measurement response that includesmultiple frequency components, and is a linear superposition of thevalues over the desired spectral range. This equivalence of time andfrequency domains is well understood by those of skill in the art. It isdescribed in textbooks on Fourier transforms such as “The FourierTransform and its Application”, 2^(nd) edition, by Ronald Bracewell,published by McGraw-Hill, incorporated herein by reference in itsentirety.

In one example, a CPV measurement made over a duration of 1 secondcontains a spectral information equivalent to 1 Hz, and corresponds tothe zone in the EIS chart that reflects ionic diffusion in solidelectrode material or in solid state electrolytes. Similarly, a partialrelaxation measurement made over a duration of a few to hundreds ofmilliseconds contains spectral information equivalent to tens tothousands of Hz, and corresponds to the zone in an EIS chart thatreflect surface charge layer(s), charge kinetics and conductorproperties.

The voltage measurement may be a measurement between two points, a firststarting point when the stimulus is applied, and second end point later.The spectral content is inversely proportional to the duration betweenthe two points. The spectral content is also influenced by the samplingrate. The voltage measurement may include M samples between these twopoints, in which case the spectral content is increased by a factor ofM/2. The desired sampling rate (and inherent spectral content) depend onmany chemical-physical processes are targeted for diagnosis.

Comparison of Response and Stimulus Signals

Measuring the voltage response and its corresponding time constantprovides a quantitative measurement of the chemical-physical processesthat take place at high frequency, e.g., film resistance or double-layercharacteristics (see FIG. 6). Various approaches may be employed togenerate and interpret response data. A system may be designed orconfigured to control parameters such as the magnitude of the appliedstimulus, the durations of the stimulus and response, and the number ofmeasurements or samples taken over these durations.

The voltage measurement may be characterized by three sets of values:the voltage amplitude at each sample point, the duration of themeasurement period, and the number of samples taken over this period.Correspondingly, the stimulus current may also be measured andcharacterized by three sets of values: the current amplitude at eachsample point, the duration of the measurement period, and the number ofsamples taken over this period. The number of samples is inverselyproportional to the maximum spectral content. The voltage and currentvalues at each sample point are related to the complex impedance valueat a particular frequency, said sampling frequency is inverselyproportional to the sampling period. The voltage and current values atthe end of the measurement period are related to the complex impedancevalue at another lower sampling frequency, with the frequency beinginversely proportional to the longer measurement period. The differencebetween the upper and lower frequencies is the bandwidth itself, relatedto the overall measurement period. Those of skill in the art understandthe relationship between sampling times, sampling frequencies andbandwidth, which is commonly used in communications theory.Consequently, such a measurement technique conducted in time domainprovides quantitative analysis of the impedance at different frequencyzones on the EIS chart without the application of frequency signals orthe use of computationally intensive frequency transforms. Frequently,implementation of time-domain measurements is more practical than theimplementation of frequency-domain measurements.

The stimulus current may be a discharge pulse of short duration,implying a high frequency stimulus for the battery. A discharge pulse ofsuch short duration has very little impact, if any, on depleting chargefrom the battery.

FIG. 7c illustrates examples of time domain acquisition ofelectrochemical data and associated frequency domain locations on aNyquist plot. The figure shows how different charging current stimuliand voltage measurements associated with different time domainscorrespond to different battery phenomena.

In a first example, a current-voltage plot for a high frequency (smalltime constant) battery probing technique is depicted in the lower leftportion of the figure. As shown, a negative pulse with a steep edgealong with a high sampling rate produces data indicative of highfrequency battery phenomena such as diffusion of ions in electrolyte.This is information associated with lower values of the real componentof impedance as illustrated in the corresponding Nyquist plot shown onthe upper portion of the drawing.

In a second example, a current-voltage plot for a lower frequency (largetime constant) battery probing technique is depicted in the lower rightportion of the figure. As shown, a positive charging pulse with ashallow edge (low slew rate) along with a low sampling rate producesdata indicative of low frequency battery phenomena such as diffusion ofions in a solid-phase electrode. This is information associated withhigher values of the real and imaginary components of impedance asillustrated in the corresponding Nyquist plot.

Remediation Operations Such as Adjustments to the Charging Process

The quantitative analysis of the impedance at different zones of the EISchart may be used as a direct mechanism to diagnose changes in thebattery's characteristics. In particular, changes in values measuredfrom cycle to cycle at a given SOC offer a particularly targeteddiagnosis of one or more physical properties of the battery and itsmaterials. For example, a change in the CPV value from cycle to cyclemay be indicative of degradation in one of the underlying batteryphysical/chemical processes and may be representative of the onset ofinternal damage to the electrode materials or the presence of metalplating. Such targeted diagnostic information may be used to modify theamplitude of the charging current in a closed loop system to address thedegraded health of the battery.

Apparatus

The apparatus used to generate time and/or frequency domain battery dataand/or analyze a battery's condition using such data may have manyconfigurations. In some cases, all or most of the measured battery data(e.g., current, voltage, and temperature) is collected by a singlemodule or circuit, while in other cases, the battery data is collectedby multiple modules and/or circuits. Battery monitoring circuits and/orcharging circuits may be used for this purpose. In some cases, thebattery control logic, whether operating alone or in conjunction withbattery monitoring and/or charging circuitry, may be used to collect thebattery data. In certain embodiments, the battery data is collected by amodule, circuit, or logic that is directly connected to a battery suchas a circuit or a module that is physically attached to, mounted on, orencased in an electronic device housing the battery. In otherembodiments, the battery data is collected by a module, circuit, orlogic that is distant from the battery and/or the electronic devicepowered by the battery. For example, the module, circuit, or logic maybe coupled to the battery and/or device by a wired or wireless link.

The apparatus that operates the battery control logic may be the sameapparatus used to collect the battery data or may be a distinctapparatus such as a mobile device, a server, or a distributed collectionof remote processing devices. In some implementations, a cloud-basedapplication is used to store and operate the battery control logic. Incertain embodiments, the apparatus used to collect battery data is alsoused to adaptively charge a battery.

FIG. 1 depicts in block form a battery monitoring/charging system thatmay be configured to obtain and analyze time and/or frequency domaindata from a battery, and, optionally, adaptively charge a battery. Theapparatus includes charging circuitry 112 that responds to controlsignals to generate a charge signal that is applied to the terminals ofthe battery. The apparatus also includes measurement circuitry 114coupled to the battery, to measure voltage, current, and/or otherbattery parameter values that may be used for adaptive charging. Controlcircuitry 116 is coupled to the charging circuitry and the measuringcircuitry. Using data received by the monitoring circuitry the controlcircuitry is configured to generate one or more control signals to adaptone or more characteristics of a charge packet in the context ofadaptive charging. In some cases, the control circuitry may also playroles in monitoring battery performance and collecting battery parametervalues.

a. Charge Circuitry

In one embodiment, charging circuitry 112 is designed and/or configuredto apply one or more charge signals to the battery in response tocontrol circuitry. The charging circuitry may include a current sourceand/or a voltage source to apply electrical charge to the terminals ofthe battery 118. The charge signals applied by the charging circuitrymay include one or more charging signals which provide a net input ofcharge or current into the battery (see, for example, FIGS. 3a and 3b )and one or more discharging signals which provide a net removal ofcharge or current from the battery (see, for example, FIGS. 3c and 3d ).

The adaptive charging circuitry and techniques may employ any chargingcircuitry, whether described herein, now known or later developed, tocharge the battery; all such charging circuitry are intended to fallwithin the scope of this disclosure. For example, charging circuitry maygenerate charge and discharge signals, packets, and pulses (as describedherein). Notably, charging circuitry is generally responsive to controlsignals from the control circuitry.

As explained above with reference to FIGS. 4a-4g , the charge anddischarge signals may include a plurality of charge packets where eachcharge packet includes one or more charge pulses and, in certainembodiments, one or more discharge pulses. The charge and dischargesignals may also include one or more discharge packets where eachdischarge charge packet includes one or more discharge pulses. Indeed,the charge and discharge signals may also include charge packets and oneor more discharge packets where each charge packet and discharge packetinclude one or more charge pulses and/or one or more discharge pulses.

In certain embodiments, the charge circuitry is designed or configuredto apply oscillating current and/or voltage signals to the battery. Suchoscillating signals may be provided at a fixed frequency, a plurality ofdiscrete frequencies, or a continuum of frequencies. As explainedelsewhere herein various frequencies stimulate distinct physicalphenomena within a battery. In certain embodiments, the charge circuitryis designed and/or configured to programmably vary the frequency ofapplied current signals to the battery.

a. Monitoring Circuitry

Monitoring circuitry 114 is designed and/or configured to measure,monitor, sense, detect and/or sample, on a continuous or periodic basis(e.g., at predetermined states of charged) one or more conditions orcharacteristics of the battery. For example, the monitoring circuitrymay measure the terminal voltage (an open circuit voltage (OCV) or aclosed circuit voltage (CCV)), the voltage response of the battery toone or more charge pulses, oscillating current of varying frequencies,and/or temperature of the battery. In one embodiment, the monitoringcircuitry includes a sensor to determine a voltage (for example, avoltmeter) and/or a sensor to determine a current (for example, acurrent meter). The monitoring circuitry provides data which isrepresentative of the condition or characteristics of the battery to thecontrol circuitry. Moreover, the monitoring circuitry may include one ormore temperature sensors which are thermally coupled to the battery togenerate, measure, and/or provide data which is representative of thetemperature of the battery. The monitoring circuitry and techniques maybe those described herein, now known or later developed, to acquire dataemployed by the control circuitry to adapt the charging profile of thebattery; all such monitoring circuitry and techniques are intended tofall within the scope of this disclosure.

a. Control Circuitry

In certain embodiments, the control circuitry 116 is designed and/orconfigured to use data from monitoring circuitry to calculate, determineand/or assess the state or condition of the battery in connection withthe charging or recharging process. For example, control circuitry maycalculate, determine and/or estimate a change in terminal voltage of thebattery in response to charge or current applied to or injected into thebattery. The control circuitry may also calculate, determine and/orestimate one, some, or all of the SOC of the battery, SOH of thebattery, partial relaxation time of the battery, overpotential of thebattery, and/or full relaxation time of the battery. The controlcircuitry may also calculate, determine and/or estimate one or morephysical characteristics of the battery or one or more batteryparameters associated with the physical characteristics. As explained,examples of battery physical characteristics include diffusion of ionsin the battery's electrolyte, diffusion of ions in one of the battery'selectrodes, reactions at the battery's anode, etc. Examples ofparameters associated with such physical characteristics includediffusion coefficients, reaction rate constants (or any order reaction),etc.

The control circuitry may also calculate, determine, and/or implement acharging sequence or charging profile based on or using one or more ofthe adaptive charging techniques and algorithms. For example, thecontrol circuitry may be configured to implement any of the charge ordischarge adjustments described herein to address actual or potentialdegradation of the battery. In this regard, control circuitry adapts,adjusts and/or controls one or more characteristics of the charge orcurrent applied to or injected into the battery (via controlling theoperation of charging circuitry) so that the terminal voltage, thechange in terminal voltage, or another battery parameter (in response tocharge or current applied to or injected into the battery during acharging or recharging sequence/operation) is within a predeterminedrange and/or below a predetermined value. In this regard, one or morecharacteristics of the charge signal may be adapted to control and/ormanage battery parameters such as the terminal voltage or a relaxationtime. In addition to adapting the sequence of charge signals, dischargesignals and rest periods—in relation to each other—the control circuitrymay vary, adjust and/or control one or more of the variablecharacteristics of a charge signal. In some cases, the control circuitrymay configured to obtain or provide a desired or predeterminedrelaxation time or period (for example, a relaxation time that is withinprescribed range), by adjusting and/or controlling the amount ofelectrical charge removed during a discharge period, the amount ofelectrical charge added during a charge period, and/or thecharacteristics of a rest period. In one embodiment, the adaptivecharging technique or algorithm employs a sequence of discharge signalswhere the relaxation time is calculated, determined and/or measuredafter each of the discharge signals. In this way, the control circuitrymay adaptively determine the total amount of electrical charge thatshould be removed (and, in response thereto, control the chargingcircuitry accordingly).

Control circuitry may include one or more processors, one or more statemachines, one or more gate arrays, programmable gate arrays and/or fieldprogrammable gate arrays, and/or a combination thereof. Indeed, controlcircuitry and monitoring circuitry may share circuitry with each otheras well as with other elements; such circuitry may be distributed amonga plurality of integrated circuits which may also perform one or moreother operations, which may be separate and distinct from that describedherein. In some embodiments, control circuitry may be housed within adevice containing the battery. Alternatively, a battery may be housed inan electronic device, while control circuitry may be housed elsewhere.For example, control circuitry may operate on a remote server or acloud-based application. In some cases, control circuitry may be coupledto monitoring circuitry and/or charging circuitry via wireless or wiredcommunication. In some cases, control circuitry may be configured tostore identified parameter values on a remote server, and in some cases,control circuitry algorithms may be updated by a user.

Control circuitry may perform or execute one or more applications,routines, programs and/or data structures that implement particularmethods, techniques, tasks or operations described and illustratedherein. The functionality of the applications, routines or programs maybe combined or distributed. In addition, the applications, routines orprograms may be implemented by control circuitry using any programminglanguage whether now known or later developed, including, for example,assembly, FORTRAN, C, C++, and BASIC, whether compiled or uncompiledcode; all of which are intended to fall within the scope of the presentdisclosure.

Additional Embodiments

It should be noted that the circuitry of the present disclosure mayinclude and/or employ the control/processing circuitry, monitoringcircuitry and/or charging circuitry described and illustrated in PCTApplication Serial No. PCT/US2012/30618, U.S. application Ser. No.13/366,352, U.S. application Ser. No. 13/626,605, U.S. application Ser.No. 13/657,841, U.S. application Ser. No. 13/747,914, all of which areincorporated herein by reference in their entireties. For the sake ofbrevity, the discussion regarding such circuitry, in the context of thetechniques of the present disclosure, will not be repeated.

The memory which stores the data, equations, relationships, instructionsfor executing battery models, and/or look-up table may be a permanent,semi-permanent or temporary (i.e., until re-programmed) storage that isdiscrete or resident on (i.e., integrated into), for example, thecontrol circuitry. As such, in one embodiment, the memory may be onetime programmable, or data, equations, relationships, and/or look-uptable employed by the control/processing circuitry may be one timeprogrammable (for example, programmed during a test or at manufacture).In another embodiment, the memory is more than one time programmableand, as such, the predetermined values and/or band limits employed bythe control circuitry may be modified after test and/or manufacture. Forexample, predetermined values and/or band limits may be modified by thecontrol logic or by a firmware update. In certain embodiments, thememory is non-transitory memory.

In some embodiments, memory for storing data, equations, executableinstructions, relationships, and/or battery parameter values may belocated on a battery unit. By having memory physically attached to abattery itself, it is possible to capture and record a battery'sparameters even when the battery is used between multiple devices. Forexample, a battery enclosure may have memory that is permanentlyattached or memory that is detachable. In some cases physically attachedmemory may be configured to communicate with the device the battery isattached to via wireless communication, e.g., a battery may have an RFIDwith memory. In some cases, a battery may be configured with connectionpins that may be used to transfer information to the device to which abattery is attached.

Many modifications, variations, combinations and/or permutations arepossible in light of the above teaching. For example, although theexemplary embodiments and/or techniques are described and/or illustratedin the context of methods and circuitry for and techniques for alithium-ion technology/chemistry based battery/cell (for example,lithium-cobalt oxide, lithium-manganese oxide, lithium-iron phosphate,and lithium-iron sulfide), the concepts described and/or illustratedherein may also be implemented in conjunction with other electrolytebattery/cell chemistries/technologies having anode(s) comprised ofaqueous or non-aqueous electrolytes, and various anode and cathodematerials. Examples of anode materials include lithium metal (e.g.,lithium metal foil), silicon or silicon alloys, and one more othermaterials including, for example, other silicon-carbon compositematerials, tin alloys, and composite tin-graphite. Electrolytes may beliquid, gel, or solid phase electrolytes. Batteries unrelated to lithiumion batteries or even intercalation batteries may be useful in thecontext of this disclosure. Examples include nickel metal hydridebatteries, nickel zinc batteries, lithium metal batteries (e.g.,lithium-sulfur batteries), and various types of solid-state batteries.Thus, it is to be understood that other embodiments may be utilized andoperational changes may be made without departing from the scope of thepresent disclosure. As such, the foregoing description of the exemplaryembodiments has been presented for the purposes of illustration anddescription. It is intended that the scope of the disclosure not belimited solely to the description above.

It should be further noted that the various circuits and circuitrydisclosed herein may be described using computer aided design tools andexpressed (or represented), as data and/or instructions embodied invarious computer-readable media, in terms of their behavioral, registertransfer, logic component, transistor, layout geometries, and/or othercharacteristics. Formats of files and other objects in which suchcircuit expressions may be implemented include, but are not limited to,formats supporting behavioral languages such as C, Verilog, and HLDL,formats supporting register level description languages like RTL, andformats supporting geometry description languages such as GDSII, GDSIII,GDSIV, CIF, MEBES and any other formats and/or languages now known orlater developed. Computer-readable media in which such formatted dataand/or instructions may be embodied include, but are not limited to,non-volatile storage media in various forms (e.g., optical, magnetic orsemiconductor storage media). Examples of transfers of such formatteddata and/or instructions include, but are not limited to, transfers(uploads, downloads, e-mail, etc.) over the Internet and/or othercomputer networks via one or more data transfer protocols (e.g., HTTP,FTP, SMTP, etc.).

Indeed, when received within a computer system via one or morecomputer-readable media, such data and/or instruction-based expressionsof the described circuits may be processed by a processing entity (e.g.,one or more processors) within the computer system in conjunction withexecution of one or more other computer programs including, withoutlimitation, net-list generation programs, place and route programs andthe like, to generate a representation or image of a physicalmanifestation of such circuits. Such representation or image maythereafter be used in device fabrication, for example, by enablinggeneration of one or more masks that are used to form various componentsof the circuits in a device fabrication process.

Moreover, the various circuits and circuitry, as well as techniques,disclosed herein may be represented via simulations using computer aideddesign and/or testing tools. The simulation of the charging circuitry,control circuitry and/or monitoring circuitry, and/or techniquesimplemented thereby, may be implemented by a computer system wherecharacteristics and operations of such circuitry, and techniquesimplemented thereby, are imitated, replicated and/or predicted via acomputer system. The present disclosure is also directed to suchsimulations of the disclosed charging circuitry, control circuitryand/or monitoring circuitry, and/or techniques implemented thereby, and,as such, are intended to fall within the scope of the presentdisclosure. The computer-readable media corresponding to suchsimulations and/or testing tools are also intended to fall within thescope of the present disclosure.

Notably, reference herein to “one embodiment” or “an embodiment” meansthat a particular feature, structure, or characteristic described inconnection with the embodiment can be included in one some or all of theembodiments of the present disclosure. The usages or appearances of thephrase “in one embodiment” or “in another embodiment” in thespecification are not referring to the same embodiment, nor are separateor alternative embodiments necessarily mutually exclusive of one or moreother embodiments. The same applies to the term “implementation.” Thepresent disclosure is neither limited to any single aspect norembodiment thereof, nor to any combinations and/or permutations of suchaspects and/or embodiments. Moreover, each of the aspects of the presentdisclosure, and/or embodiments thereof, may be employed alone or incombination with one or more of the other aspects of the presentdisclosure and/or embodiments thereof. For the sake of brevity, certainpermutations and combinations are not discussed and/or illustratedseparately herein.

Further, an embodiment or implementation described herein as exemplaryis not to be construed as preferred or advantageous, for example, overother embodiments or implementations; rather, it is intended to conveyor indicate that the embodiment or the embodiments are exampleembodiment(s).

In the claims, the term “determine” and “calculate” and other formsthereof (i.e., determining, determined and the like or calculating,calculated and the like) means, among other things, calculate, assesses,determine and/or estimate and other forms thereof.

Moreover, the phrase “determining a state of charge of the battery” and“calculating a state of charge of the battery” in the claims meansdetermining, detecting, calculating, estimating, and/or measuring astate of charge of the battery and/or a change in a state of charge ofthe battery/cell. Similarly, the phrase “calculating a state of healthof the battery” and “determining a state of health of the battery” inthe claims means determining, detecting, calculating, estimating, and/ormeasuring a state of health of the battery and/or a change in a state ofhealth of the battery/cell.

In addition, the terms “first,” “second,” and the like, herein do notdenote any order, quantity, or importance, but rather are used todistinguish one element from another. Moreover, the terms “a” and “an”herein do not denote a limitation of quantity, but rather denote thepresence of at least one of the referenced item. Further, the term“data” may mean, among other things, a current or voltage signal(s)whether in analog or a digital form (which may be a single bit (or thelike) or multiple bits (or the like)).

As used in the claims, the terms “comprises,” “comprising,” “includes,”“including,” “have,” and “having” or any other variation thereof, areintended to cover a non-exclusive inclusion, such that a process,method, article, or apparatus that comprises a list of elements does notinclude only those elements but may include other elements not expresslylisted or inherent to such process, method, article, or apparatus.

Further, the statement that one or more circuits, circuitry, nodesand/or components are “coupled” means that the circuits, circuitry,nodes and/or components are joined and/or operate (for example,physically or electrically) together either directly or indirectly,i.e., through one or more intermediate circuits, circuitry, nodes and/orcomponents, so long as a link occurs; “directly coupled” means that twoelements are directly joined, in contact and/or operate with each other.

The claim elements that do not recite “means” or “step” are not in“means plus function” or “step plus function” form. (See, 35 USC §112(f)). Applicant intend that only claim elements reciting “means” or“step” be interpreted under or in accordance with 35 U.S.C. § 112(f).

What is claimed is:
 1. A method of adaptively charging a battery, themethod comprising: (a) measuring a battery response during a time regimeor a frequency regime where the battery's response reflects a physicalphenomenon occurring in the battery; (b) using the battery's response,as measured in (a), to characterize the physical phenomenon; and (c)based on the physical phenomenon's characterization, as determined in(b), performing at least one of: (1) generating a diagnosis of acondition of the battery; or (2) adapting a charging process of thebattery.
 2. The method of claim 1, further comprising, prior to (a),applying a stimulus to the battery, wherein the battery responsecomprises a response of the battery to the stimulus.
 3. The method ofclaim 2, wherein the stimulus is applied during discharge of thebattery.
 4. The method of claim 1, wherein adapting the charging processof the battery comprises at least one of: (1) modifying an amount ofcharge removed by a discharge pulse utilized in the charging process;(2) modifying a rate or shape of a decay of a terminal voltage of thebattery; or (3) modify a rate or amount of charge injected duringcharging of the battery.
 5. The method of claim 1, whereincharacterizing the physical phenomenon occurring in the battery occursin a cloud device remote from the battery.
 6. The method of claim 5,further comprising transmitting parameters determined based on thecharacterized physical phenomenon to charging circuitry of the batteryvia a wireless link.
 7. The method of claim 1, wherein the batterycomprises multiple cells connected in series and/or in parallel.
 8. Themethod of claim 1, wherein characterizing the physical phenomenon in (b)comprises a comparison of battery data, including the battery's responsemeasured in (a), across multiple charging cycles.
 9. The method of claim8, wherein the comparison occurs at a given state of charge (SOC). 10.The method of claim 1, wherein (b) comprises determining a charge pulsevoltage from the battery's response to characterize transport of metalions in an electrode of the battery.
 11. The method of claim 1, wherein(b) comprises determining a partial relaxation time from the battery'sresponse to characterize transport of metal ions in an electrolyte ofthe battery.
 12. The method of claim 1, wherein the physical phenomenoncomprises a chemical or electrochemical reaction in or on an electrodeof the battery.
 13. A system for adaptively charging a battery, thesystem comprising: charging and/or monitoring circuitry designed orconfigured to apply a charge signal to the battery; and controlcircuitry, coupled to the charging and/or monitoring circuitry, andconfigured to cause the system to: (a) measure a battery response duringa time regime or a frequency regime where the battery's responsereflects a physical phenomenon occurring in the battery; (b) use thebattery's response, as measured in (a), to characterize the physicalphenomenon; and (c) based on the physical phenomenon's characterization,as determined in (b), perform at least one of: (1) generating adiagnosis of a condition of the battery; or (2) adapting a chargingprocess of the battery.
 14. The system of claim 13, wherein the controlcircuitry is further configured to, prior to (a), apply a stimulus tothe battery, wherein the battery response comprises a response of thebattery to the stimulus.
 15. The system of claim 14, wherein thestimulus is applied during discharge of the battery.
 16. The system ofclaim 13, wherein to adapt the charging process of the battery, thecontrol circuitry is configured to cause the system to perform at leastone of: (1) modifying an amount of charge removed by a discharge pulseutilized in the charging process; (2) modifying a rate or shape of adecay of a terminal voltage of the battery; or (3) modify a rate oramount of charge injected during charging of the battery.
 17. The systemof claim 13, wherein characterizing the physical phenomenon occurring inthe battery occurs in a cloud device remote from the battery.
 18. Thesystem of claim 17, wherein the control circuitry is further configuredto transmit parameters determined based on the characterized physicalphenomenon to charging circuitry of the battery via a wireless link. 19.The system of claim 13, wherein the battery comprises multiple cellsconnected in series and/or in parallel.
 20. The system of claim 13,wherein characterizing the physical phenomenon in (b) comprises acomparison of battery data, including the battery's response measured in(a), across multiple charging cycles.
 21. The system of claim 20,wherein the comparison occurs at a given state of charge (SOC).
 22. Thesystem of claim 13, wherein (b) comprises determining a charge pulsevoltage from the battery's response to characterize transport of metalions in an electrode of the battery.
 23. The system of claim 13, wherein(b) comprises determining a partial relaxation time from the battery'sresponse to characterize transport of metal ions in an electrolyte ofthe battery.
 24. The system of claim 13, wherein the physical phenomenoncomprises a chemical or electrochemical reaction in or on an electrodeof the battery.